{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":23317,"offset":23307,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"\u0412\u0430\u0448 \u043a\u043e\u0434 \u2014 **\u043d\u0430 C++**, \u0442\u0430\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442\u0441\u044f `std::vector`, \u043f\u0440\u0438\u0441\u0432\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440 (\u043a\u043e\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 `rknn_tensor_attr`), \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043d\u0443\u043b\u0451\u043c \u0447\u0435\u0440\u0435\u0437 `memset` \u2014 \u044d\u0442\u043e \u0432\u0441\u0435 \u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u043e \u0434\u043b\u044f C, \u043a\u0440\u043e\u043c\u0435 `std::vector`, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u2014 \u0447\u0438\u0441\u0442\u043e C++ \u0438 \u043e\u0442\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u0435\u0442 \u0432 C.\n\n---\n\n### \u0413\u043b\u0430\u0432\u043d\u044b\u0435 \u0437\u0430\u043c\u0435\u0447\u0430\u043d\u0438\u044f \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u0445\u043e\u0434\u0430 \u043d\u0430 \"\u0447\u0438\u0441\u0442\u044b\u0439 C\":\n\n1. **\u041d\u0435\u0442 `std::vector` \u0432 C** \n \u041d\u0443\u0436\u043d\u043e \u0437\u0430\u043c\u0435\u043d\u0438\u0442\u044c `std::vector out_zps;` \u0438 `std::vector out_scales;` \u043d\u0430 \u043e\u0431\u044b\u0447\u043d\u044b\u0435 \u043c\u0430\u0441\u0441\u0438\u0432\u044b \u0438\u043b\u0438 \u0443\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u0438 \u0438 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u044d\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u0432.\n\n2. **\u041f\u0440\u0438\u0441\u0432\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440 rknn_tensor_attr \u2014 \u0434\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u043e \u0438 \u0432 C** \n \u0421\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u043d\u043e\u0435 \u043f\u0440\u0438\u0441\u0432\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u0432 C, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u043c\u043e\u0436\u043d\u043e \u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0442\u044c.\n\n3. **\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `nullptr` / NULL & std::memset \u2014 \u0432\u0441\u0451 \u0432 \u043f\u043e\u0440\u044f\u0434\u043a\u0435.**\n\n---\n\n## \u0418\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u043d\u0430\u044f \u0432\u0435\u0440\u0441\u0438\u044f \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u0438 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043f\u043e\u0434 \u0447\u0438\u0441\u0442\u044b\u0439 C\n\n```c\n#include \n#include \n#include \n#include \"rknn_api.h\"\n\n// \u041c\u0430\u043a\u0441 \u0432\u044b\u0445\u043e\u0434\u043e\u0432, \u0432\u044b\u0441\u0442\u0430\u0432\u044c\u0442\u0435 \u043f\u043e \u0444\u0430\u043a\u0442\u0443 \u0443 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043e\u0431\u044b\u0447\u043d\u043e 3\n#define MAX_OUTPUT_NUM 3\n\ntypedef struct {\n rknn_context ctx;\n rknn_tensor_attr input_attr;\n rknn_tensor_attr output_attrs[MAX_OUTPUT_NUM];\n rknn_tensor_mem *input_mem;\n rknn_tensor_mem *output_mems[MAX_OUTPUT_NUM];\n int n_output;\n int img_width;\n int img_height;\n int32_t out_zps[MAX_OUTPUT_NUM];\n float out_scales[MAX_OUTPUT_NUM];\n} RKNNContext;\n\nint init_rknn_model(RKNNContext *rknn_ctx, const char *model_path)\n{\n memset(rknn_ctx, 0, sizeof(RKNNContext));\n\n int ret = rknn_init(&rknn_ctx->ctx, model_path, 0, 0, NULL);\n if (ret < 0) {\n printf(\"rknn_init fail! ret=%d\\n\", ret);\n return -1;\n }\n\n rknn_input_output_num io_num;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_IN_OUT_NUM, &io_num, sizeof(io_num));\n if (ret != RKNN_SUCC) return -1;\n\n if (io_num.n_input < 1 || io_num.n_output > MAX_OUTPUT_NUM) {\n printf(\"Invalid input/output num\\n\");\n return -1;\n }\n\n // \u041f\u043e\u043b\u0443\u0447\u0430\u0435\u043c input_attr (\u0442\u043e\u043b\u044c\u043a\u043e \u043f\u0435\u0440\u0432\u044b\u0439 \u0432\u0445\u043e\u0434)\n rknn_tensor_attr input_attrs[io_num.n_input];\n for (uint32_t i = 0; i < io_num.n_input; i++) {\n input_attrs[i].index = i;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_INPUT_ATTR, &input_attrs[i], sizeof(rknn_tensor_attr));\n if (ret != RKNN_SUCC) return -1;\n }\n rknn_ctx->input_attr = input_attrs[0];\n rknn_ctx->img_width = rknn_ctx->input_attr.dims[2];\n rknn_ctx->img_height = rknn_ctx->input_attr.dims[1];\n\n rknn_ctx->input_attr.type = RKNN_TENSOR_UINT8;\n rknn_ctx->input_attr.fmt = RKNN_TENSOR_NHWC;\n rknn_ctx->input_mem = rknn_create_mem(rknn_ctx->ctx, rknn_ctx->input_attr.size_with_stride);\n if (!rknn_ctx->input_mem) {\n printf(\"Failed to create input mem\\n\");\n return -1;\n }\n\n // \u041f\u043e\u043b\u0443\u0447\u0430\u0435\u043c \u0432\u044b\u0445\u043e\u0434\u044b\n for (uint32_t i = 0; i < io_num.n_output; i++) {\n rknn_ctx->output_attrs[i].index = i;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_NATIVE_NHWC_OUTPUT_ATTR, &rknn_ctx->output_attrs[i], sizeof(rknn_tensor_attr));\n if (ret != RKNN_SUCC) return -1;\n\n rknn_ctx->output_mems[i] = rknn_create_mem(rknn_ctx->ctx, rknn_ctx->output_attrs[i].size_with_stride);\n if (!rknn_ctx->output_mems[i]) {\n printf(\"Failed to create output mem #%d\\n\", i);\n return -1;\n }\n\n ret = rknn_set_io_mem(rknn_ctx->ctx, rknn_ctx->output_mems[i], &rknn_ctx->output_attrs[i]);\n if (ret < 0) return -1;\n\n rknn_ctx->out_zps[i] = rknn_ctx->output_attrs[i].zp;\n rknn_ctx->out_scales[i] = rknn_ctx->output_attrs[i].scale;\n }\n\n rknn_ctx->n_output = io_num.n_output;\n\n // \u0423\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u0435\u043c input \u043c\u0435\u043c\u043e\n ret = rknn_set_io_mem(rknn_ctx->ctx, rknn_ctx->input_mem, &rknn_ctx->input_attr);\n if (ret < 0) return -1;\n\n return 0;\n}\n\nvoid release_rknn_model(RKNNContext *rknn_ctx)\n{\n if (rknn_ctx->input_mem)\n rknn_destroy_mem(rknn_ctx->ctx, rknn_ctx->input_mem);\n\n for (int i = 0; i < rknn_ctx->n_output; i++) {\n if (rknn_ctx->output_mems[i])\n rknn_destroy_mem(rknn_ctx->ctx, rknn_ctx->output_mems[i]);\n }\n\n if (rknn_ctx->ctx)\n rknn_destroy(rknn_ctx->ctx);\n\n memset(rknn_ctx, 0, sizeof(RKNNContext));\n}\n\nvoid resize_and_copy_frame_to_input(AVFrame *rgb_frame, RKNNContext *rknn_ctx)\n{\n int width = rknn_ctx->img_width;\n int height = rknn_ctx->img_height;\n int channels = 3; // RGB24\n uint8_t *dst_ptr = (uint8_t *)rknn_ctx->input_mem->virt_addr;\n int stride = rknn_ctx->input_attr.w_stride;\n\n if (stride == width) {\n memcpy(dst_ptr, rgb_frame->data[0], width * height * channels);\n } else {\n int src_stride = rgb_frame->linesize[0];\n for (int h = 0; h < height; ++h) {\n memcpy(dst_ptr + h * stride * channels, rgb_frame->data[0] + h * src_stride, width * channels);\n }\n }\n}\n```\n\n---\n\n### \u041a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u043c\u043e\u043c\u0435\u043d\u0442\u044b:\n\n- \u0417\u0430\u043c\u0435\u043d\u0435\u043d\u044b `std::vector` \u043d\u0430 \u043e\u0431\u044b\u0447\u043d\u044b\u0435 \u043c\u0430\u0441\u0441\u0438\u0432\u044b \u0441 `MAX_OUTPUT_NUM` \u0434\u043b\u0438\u043d\u043e\u0439 (\u0437\u0430\u0440\u0430\u043d\u0435\u0435 \u0438\u0437\u0432\u0435\u0441\u0442\u043d\u043e\u0435 \u0447\u0438\u0441\u043b\u043e \u0432\u044b\u0445\u043e\u0434\u043e\u0432 \u2014 \u043e\u0431\u044b\u0447\u043d\u043e 3).\n- \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d `int32_t` \u0438 `float` \u0434\u043b\u044f \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432 \u043f\u043e\u0434 `out_zps` \u0438 `out_scales`.\n- \u0414\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0430 \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0430 \u043d\u0430 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0432\u0445\u043e\u0434\u043e\u0432/\u0432\u044b\u0445\u043e\u0434\u043e\u0432.\n- \u0414\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u044b \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438 \u043d\u0430 \u0443\u0441\u043f\u0435\u0448\u043d\u043e\u0435 \u0432\u044b\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u043f\u0430\u043c\u044f\u0442\u0438.\n\n---\n\n\u0415\u0441\u043b\u0438 \u043d\u0443\u0436\u0435\u043d \u043f\u0440\u0438\u043c\u0435\u0440 \u043a\u043e\u0434\u0430 \u0432\u044b\u0437\u043e\u0432\u0430 RKNN \u0432 \u0442\u0430\u043a\u043e\u043c \u0441\u0442\u0438\u043b\u0435 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432 \u0446\u0438\u043a\u043b\u0435 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u043a\u0430\u0434\u0440\u043e\u0432) \u2014 \u043c\u043e\u0433\u0443 \u0434\u043e\u0431\u0430\u0432\u0438\u0442\u044c.\n\n---\n\n### \u0418\u0442\u043e\u0433\n\n**\u0412\u0430\u0448 \u043a\u043e\u0434 \u043d\u0430 \u0447\u0438\u0441\u0442\u043e\u043c \u0421\u0418 \u2014 \u0441 \u0443\u0447\u0451\u0442\u043e\u043c \u0438\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u044f `std::vector` \u2014 \u043f\u0440\u0438\u0432\u0435\u0434\u0451\u043d \u0432\u044b\u0448\u0435.** \n\u0415\u0433\u043e \u043c\u043e\u0436\u043d\u043e \u0441\u043c\u0435\u043b\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0432 \u0432\u0430\u0448\u0435\u043c \u043f\u0440\u043e\u0435\u043a\u0442\u0435 \u0441 FFmpeg \u0438 RKNN.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":9532,"n_turns_in_conversation":10,"n_words":970,"source_row_offset":23307,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"54831554a81977de91874b21","turn_index":2,"user_text":"\u041f\u0440\u043e\u0432\u0435\u0440\u044c \u043a\u043e\u0434 - \u041c\u043d\u0435 \u043d\u0430\u0434\u043e \u043d\u0430 \u0447\u0438\u0441\u0442\u043e\u043c \u0421\u0418\n\n// - \u041e\u0431\u044a\u044f\u0432\u0438\u043c \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0443 \u0434\u043b\u044f \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0430 \u043c\u043e\u0434\u0435\u043b\u0438 (\u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435, \u0438\u0441\u0445\u043e\u0434\u044f \u0438\u0437 \u0432\u0430\u0448\u0435\u0433\u043e \u043a\u043e\u0434\u0430):\ntypedef struct {\n rknn_context ctx;\n rknn_tensor_attr input_attr;\n rknn_tensor_attr output_attrs[3];\n rknn_tensor_mem *input_mem;\n rknn_tensor_mem *output_mems[3];\n int n_output;\n int img_width;\n int img_height;\n std::vector out_zps;\n std::vector out_scales;\n} RKNNContext;\n\n// \u0418\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f RKNN \u0441 \u043c\u043e\u0434\u0435\u043b\u044c\u044e - \u043f\u043e\u0447\u0442\u0438 \u0432\u0430\u0448 \u043a\u043e\u0434 \u0438\u0437 main, \u0443\u043f\u0440\u043e\u0449\u0435\u043d\u043d\u044b\u0439 \u043f\u043e\u0434 \u043d\u0443\u0436\u0434\u044b \u043f\u043e\u0442\u043e\u043a\u0430:\nint init_rknn_model(RKNNContext *rknn_ctx, const char *model_path)\n{\n memset(rknn_ctx, 0, sizeof(RKNNContext));\n \n int ret = rknn_init(&rknn_ctx->ctx, model_path, 0, 0, NULL);\n if (ret < 0) {\n printf(\"rknn_init fail! ret=%d\\n\", ret);\n return -1;\n }\n\n // \u041f\u043e\u043b\u0443\u0447\u0430\u0435\u043c \u0438\u043d\u0444\u043e \u043e \u0432\u0445\u043e\u0434\u0430\u0445/\u0432\u044b\u0445\u043e\u0434\u0430\u0445\n rknn_input_output_num io_num;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_IN_OUT_NUM, &io_num, sizeof(io_num));\n if (ret != RKNN_SUCC) return -1;\n\n rknn_tensor_attr input_attrs[io_num.n_input];\n for (uint32_t i = 0; i < io_num.n_input; i++) {\n input_attrs[i].index = i;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_INPUT_ATTR, &input_attrs[i], sizeof(rknn_tensor_attr));\n if (ret != RKNN_SUCC) return -1;\n }\n\n // \u0421\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u043c \u0442\u043e\u043b\u044c\u043a\u043e \u043f\u0435\u0440\u0432\u044b\u0439 input_attr (\u0447\u0430\u0441\u0442\u043e \u043c\u043e\u0434\u0435\u043b\u044c \u043e\u0434\u0438\u043d \u0432\u0445\u043e\u0434)\n rknn_ctx->input_attr = input_attrs[0];\n rknn_ctx->img_width = rknn_ctx->input_attr.dims[2];\n rknn_ctx->img_height = rknn_ctx->input_attr.dims[1];\n\n // \u0421\u043e\u0437\u0434\u0430\u0435\u043c input_mem (\u043f\u0440\u0435\u0434\u043f\u043e\u043b\u0430\u0433\u0430\u0435\u043c NHWC + UINT8, \u043a\u0430\u043a \u0432 \u0432\u0430\u0448\u0435\u043c \u043a\u043e\u0434\u0435)\n rknn_ctx->input_attr.type = RKNN_TENSOR_UINT8;\n rknn_ctx->input_attr.fmt = RKNN_TENSOR_NHWC;\n rknn_ctx->input_mem = rknn_create_mem(rknn_ctx->ctx, rknn_ctx->input_attr.size_with_stride);\n\n // \u0412\u044b\u0445\u043e\u0434\u044b (\u0432\u043e\u0437\u044c\u043c\u0435\u043c 3 \u0432\u044b\u0445\u043e\u0434\u0430, \u043a\u0430\u043a \u0432 \u0432\u0430\u0448\u0435\u043c \u043a\u043e\u0434\u0435)\n rknn_tensor_attr output_attrs[io_num.n_output];\n memset(output_attrs, 0, sizeof(output_attrs));\n for (uint32_t i = 0; i < io_num.n_output; i++) {\n output_attrs[i].index = i;\n ret = rknn_query(rknn_ctx->ctx, RKNN_QUERY_NATIVE_NHWC_OUTPUT_ATTR, &output_attrs[i], sizeof(rknn_tensor_attr));\n if (ret != RKNN_SUCC) return -1;\n rknn_ctx->output_attrs[i] = output_attrs[i];\n rknn_ctx->output_mems[i] = rknn_create_mem(rknn_ctx->ctx, output_attrs[i].size_with_stride);\n\n rknn_ctx->out_zps.push_back(output_attrs[i].zp);\n rknn_ctx->out_scales.push_back(output_attrs[i].scale);\n\n ret = rknn_set_io_mem(rknn_ctx->ctx, rknn_ctx->output_mems[i], &rknn_ctx->output_attrs[i]);\n if (ret < 0) return -1;\n }\n rknn_ctx->n_output = io_num.n_output;\n\n ret = rknn_set_io_mem(rknn_ctx->ctx, rknn_ctx->input_mem, &rknn_ctx->input_attr);\n if (ret < 0) return -1;\n\n return 0;\n}\n\nvoid release_rknn_model(RKNNContext *rknn_ctx)\n{\n if (rknn_ctx->input_mem) rknn_destroy_mem(rknn_ctx->ctx, rknn_ctx->input_mem);\n for (int i = 0; i < rknn_ctx->n_output; i++) {\n if (rknn_ctx->output_mems[i]) rknn_destroy_mem(rknn_ctx->ctx, rknn_ctx->output_mems[i]);\n }\n if (rknn_ctx->ctx) rknn_destroy(rknn_ctx->ctx);\n memset(rknn_ctx, 0, sizeof(RKNNContext));\n}\n\n// \u0424\u0443\u043d\u043a\u0446\u0438\u044f \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0430\u0446\u0438\u0438 \u0438\u0437 AVFrame RGB24 -> input_mem (\u043f\u0440\u0435\u0434\u043f\u043e\u043b\u0430\u0433\u0430\u0435\u043c NHWC uint8)\n// input_mem->virt_addr - \u0443\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u044c \u0431\u0443\u0444\u0435\u0440\u0430 \u043c\u043e\u0434\u0435\u043b\u0438\nvoid resize_and_copy_frame_to_input(AVFrame *rgb_frame, RKNNContext *rknn_ctx)\n{\n // \u0415\u0441\u043b\u0438 \u0440\u0430\u0437\u043c\u0435\u0440 \u043a\u0430\u0434\u0440\u0430 rgb_frame \u043d\u0435 \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u0435\u0442 \u0441 \u043c\u043e\u0434\u0435\u043b\u044c\u043d\u044b\u043c \u2014 resize\n // \u0422\u0443\u0442 \u0443\u0436\u0435 rgb_frame \u2014 INPUT_WIDTH x INPUT_HEIGHT\n // \u0415\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0442\u044c \u0440\u0430\u0437\u043d\u043e\u0435, \u043d\u0430\u0434\u043e \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c resize \u0447\u0435\u0440\u0435\u0437 stbir_resize_uint8 \u0438\u043b\u0438 sws_scale\n\n int width = rknn_ctx->img_width;\n int height = rknn_ctx->img_height;\n int channels = 3; // RGB24\n\n uint8_t *dst_ptr = (uint8_t *)rknn_ctx->input_mem->virt_addr;\n\n // \u0415\u0441\u043b\u0438 stride == width, \u043a\u043e\u043f\u0438\u0440\u0443\u0435\u043c \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e\n int stride = rknn_ctx->input_attr.w_stride;\n if (stride == width) {\n memcpy(dst_ptr, rgb_frame->data[0], width * height * channels);\n } else {\n // \u043a\u043e\u043f\u0438\u0440\u0443\u0435\u043c \u043f\u043e\u0441\u0442\u0440\u043e\u0447\u043d\u043e \u0441 \u0443\u0447\u0435\u0442\u043e\u043c stride\n int src_stride = rgb_frame->linesize[0];\n for (int h = 0; h < height; ++h) {\n memcpy(dst_ptr + h * stride * channels, rgb_frame->data[0] + h * src_stride, width * channels);\n }\n }\n}"},{"assistant_initiates":false,"asst_text":"\u041d\u0438\u0436\u0435 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d \u043f\u0440\u0438\u043c\u0435\u0440 \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u0430 \u0432\u0430\u0448\u0435\u0433\u043e \u043a\u043e\u0434\u0430 (\u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 std::vector, std::set \u0438 \u0434\u0440\u0443\u0433\u0438\u0435 C++ \u043a\u043e\u043d\u0441\u0442\u0440\u0443\u043a\u0446\u0438\u0438) \u0432 **\u0447\u0438\u0441\u0442\u044b\u0439 C** \u0431\u0435\u0437 STL, \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432 \u0447\u0435\u0440\u0435\u0437 malloc/realloc \u0438 \u043d\u0430\u0438\u0432\u043d\u043e\u0439 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u043e\u0432 \u0434\u043b\u044f NMS.\n\n---\n\n# \u041a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u0438\u0434\u0435\u0438 \u043f\u0435\u0440\u0435\u0445\u043e\u0434\u0430 \u043d\u0430 \u0447\u0438\u0441\u0442\u044b\u0439 C:\n\n- \u0417\u0430\u043c\u0435\u043d\u044f\u0435\u043c `std::vector` \u043d\u0430 \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u043c\u0430\u0441\u0441\u0438\u0432 `float*` \u0441 \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0435\u043c \u0440\u0430\u0437\u043c\u0435\u0440\u0430 \u0438 \u0434\u043b\u0438\u043d\u044b.\n- \u0417\u0430\u043c\u0435\u043d\u044f\u0435\u043c `std::vector` \u043d\u0430 `int*`.\n- \u0412\u043c\u0435\u0441\u0442\u043e `std::set` \u043c\u043e\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u043c\u0430\u0441\u0441\u0438\u0432 \u0441 \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u043e\u0439 \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u0438.\n- \u0420\u0435\u043a\u0443\u0440\u0441\u0438\u0432\u043d\u044b\u0439 `quick_sort_indice_inverse` \u0440\u0435\u0430\u043b\u0438\u0437\u0443\u0435\u043c \u0441 \u043c\u0430\u0441\u0441\u0438\u0432\u0430\u043c\u0438.\n- \u0423\u0431\u0438\u0440\u0430\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `inline static` \u2014 \u0437\u0430\u043c\u0435\u043d\u044f\u0435\u043c \u043d\u0430 `static` (\u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e `inline` \u043f\u043e\u0434\u043d\u0438\u043c\u0430\u0435\u0442\u0441\u044f \u043a\u043e\u043c\u043f\u0438\u043b\u044f\u0442\u043e\u0440\u043e\u043c).\n- \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c C-\u043a\u043e\u043c\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0438 \u0438 \u0441\u0442\u0440\u043e\u0433\u0438\u0439 \u0441\u0442\u0438\u043b\u044c C.\n- \u0414\u043b\u044f `strncpy` \u0432\u044b\u0432\u043e\u0434\u0438\u043c \u043f\u0440\u043e\u0441\u0442\u043e \u043a\u0430\u043a \u0435\u0441\u0442\u044c, \u0443\u0431\u0435\u0434\u0438\u0442\u0435\u0441\u044c \u0447\u0442\u043e `OBJ_NAME_MAX_SIZE` \u0438 `OBJ_CLASS_NUM` \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u044b.\n\n---\n\n# \u041f\u043e\u043b\u043d\u044b\u0439 \u043f\u0440\u0438\u043c\u0435\u0440 \u043d\u0430 \u0447\u0438\u0441\u0442\u043e\u043c C:\n\n```c\n#include \n#include \n#include \n#include \n#include \n\n#define LABEL_NALE_TXT_PATH \"./model/coco_80_labels_list.txt\"\n#define OBJ_CLASS_NUM 80\n#define OBJ_NAME_MAX_SIZE 64\n#define OBJ_NUMB_MAX_SIZE 512\n#define PROP_BOX_SIZE 85 // \u041e\u0431\u044b\u0447\u043d\u043e 5 + 80 \u043a\u043b\u0430\u0441\u0441\u043e\u0432\n\ntypedef struct {\n int left, top, right, bottom;\n} box_t;\n\ntypedef struct {\n char name[OBJ_NAME_MAX_SIZE];\n box_t box;\n float prop;\n} detect_result_t;\n\ntypedef struct {\n detect_result_t results[OBJ_NUMB_MAX_SIZE];\n int count;\n} detect_result_group_t;\n\nstatic char *labels[OBJ_CLASS_NUM];\n\n// \u044f\u043a\u043e\u0440\u044f\nstatic const int anchor0[6] = {10, 13, 16, 30, 33, 23};\nstatic const int anchor1[6] = {30, 61, 62, 45, 59, 119};\nstatic const int anchor2[6] = {116, 90, 156, 198, 373, 326};\n\nstatic int clamp_i(float val, int min, int max)\n{\n if (val < min) return min;\n if (val > max) return max;\n return (int)val;\n}\n\n// --- \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043c\u0430\u0441\u0441\u0438\u0432\u044b ---------------------------------------------------\ntypedef struct {\n float *data;\n int count;\n int capacity;\n} float_array;\n\ntypedef struct {\n int *data;\n int count;\n int capacity;\n} int_array;\n\nstatic void float_array_init(float_array *arr)\n{\n arr->data = NULL;\n arr->count = 0;\n arr->capacity = 0;\n}\n\nstatic void float_array_free(float_array *arr)\n{\n if (arr->data) free(arr->data);\n arr->data = NULL;\n arr->count = 0;\n arr->capacity = 0;\n}\n\nstatic int float_array_push(float_array *arr, float val)\n{\n if (arr->count >= arr->capacity)\n {\n int new_cap = arr->capacity == 0 ? 64 : arr->capacity * 2;\n float *tmp = (float *)realloc(arr->data, new_cap * sizeof(float));\n if (!tmp) return -1;\n arr->data = tmp;\n arr->capacity = new_cap;\n }\n arr->data[arr->count++] = val;\n return 0;\n}\n\nstatic void int_array_init(int_array *arr)\n{\n arr->data = NULL;\n arr->count = 0;\n arr->capacity = 0;\n}\n\nstatic void int_array_free(int_array *arr)\n{\n if (arr->data) free(arr->data);\n arr->data = NULL;\n arr->count = 0;\n arr->capacity = 0;\n}\n\nstatic int int_array_push(int_array *arr, int val)\n{\n if (arr->count >= arr->capacity)\n {\n int new_cap = arr->capacity == 0 ? 64 : arr->capacity * 2;\n int *tmp = (int *)realloc(arr->data, new_cap * sizeof(int));\n if (!tmp) return -1;\n arr->data = tmp;\n arr->capacity = new_cap;\n }\n arr->data[arr->count++] = val;\n return 0;\n}\n\n// --- \u043a\u043e\u043d\u0435\u0446 \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432 ---------------------------------------------\n\n// \u0424\u0443\u043d\u043a\u0446\u0438\u044f \u0447\u0442\u0435\u043d\u0438\u044f \u0441\u0442\u0440\u043e\u043a \u0438 \u0437\u0430\u0433\u0440\u0443\u0437\u043a\u0438 \u043c\u0435\u0442\u043e\u043a \u0432 labels - \u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0439\u0442\u0435 \u0432\u0430\u0448\u0443 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044e\n\n// CalculateOverlap\nstatic float CalculateOverlap(float xmin0, float ymin0, float xmax0, float ymax0,\n float xmin1, float ymin1, float xmax1, float ymax1)\n{\n float w = fmaxf(0.f, fminf(xmax0, xmax1) - fmaxf(xmin0, xmin1) + 1.0f);\n float h = fmaxf(0.f, fminf(ymax0, ymax1) - fmaxf(ymin0, ymin1) + 1.0f);\n float i = w * h;\n float u = (xmax0 - xmin0 + 1.0f) * (ymax0 - ymin0 + 1.0f) + (xmax1 - xmin1 + 1.0f) * (ymax1 - ymin1 + 1.0f) - i;\n return u <= 0.f ? 0.f : (i / u);\n}\n\n// NMS \u0441 \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u043c\u0430\u0441\u0441\u0438\u0432\u0430\u043c\u0438\nstatic void nms(int validCount, float_array *outputLocations, int_array *classIds, int *order, int filterId, float threshold)\n{\n for (int i = 0; i < validCount; ++i)\n {\n if (order[i] == -1 || classIds->data[i] != filterId)\n continue;\n int n = order[i];\n for (int j = i + 1; j < validCount; ++j)\n {\n int m = order[j];\n if (m == -1 || classIds->data[j] != filterId)\n continue;\n\n float xmin0 = outputLocations->data[n * 4 + 0];\n float ymin0 = outputLocations->data[n * 4 + 1];\n float xmax0 = outputLocations->data[n * 4 + 0] + outputLocations->data[n * 4 + 2];\n float ymax0 = outputLocations->data[n * 4 + 1] + outputLocations->data[n * 4 + 3];\n\n float xmin1 = outputLocations->data[m * 4 + 0];\n float ymin1 = outputLocations->data[m * 4 + 1];\n float xmax1 = outputLocations->data[m * 4 + 0] + outputLocations->data[m * 4 + 2];\n float ymax1 = outputLocations->data[m * 4 + 1] + outputLocations->data[m * 4 + 3];\n\n float iou = CalculateOverlap(xmin0, ymin0, xmax0, ymax0, xmin1, ymin1, xmax1, ymax1);\n\n if (iou > threshold)\n order[j] = -1;\n }\n }\n}\n\n// \u0411\u044b\u0441\u0442\u0440\u0430\u044f \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u0441 \u043c\u0430\u0441\u0441\u0438\u0432\u0430\u043c\u0438\nstatic void quick_sort_indice_inverse(float_array *input, int left, int right, int *indices)\n{\n if (left >= right)\n return;\n\n float key = input->data[left];\n int key_index = indices[left];\n int low = left;\n int high = right;\n\n while (low < high)\n {\n while (low < high && input->data[high] <= key) --high;\n input->data[low] = input->data[high];\n indices[low] = indices[high];\n\n while (low < high && input->data[low] >= key) ++low;\n input->data[high] = input->data[low];\n indices[high] = indices[low];\n }\n\n input->data[low] = key;\n indices[low] = key_index;\n\n quick_sort_indice_inverse(input, left, low - 1, indices);\n quick_sort_indice_inverse(input, low + 1, right, indices);\n}\n\nstatic int8_t qnt_f32_to_affine(float f32, int32_t zp, float scale)\n{\n float dst_val = (f32 / scale) + zp;\n if (dst_val < -128) dst_val = -128;\n if (dst_val > 127) dst_val = 127;\n return (int8_t)dst_val;\n}\n\nstatic float deqnt_affine_to_f32(int8_t qnt, int32_t zp, float scale)\n{\n return ((float)qnt - (float)zp) * scale;\n}\n\n// \u041f\u0440\u0438\u043c\u0435\u0440 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 process_native_nhwc (\u0430\u0434\u0430\u043f\u0442\u0430\u0446\u0438\u044f \u043f\u043e\u0434 C, \u0441 dynamic arrays).\n// \u0414\u043e\u0431\u0430\u0432\u043b\u044f\u0439\u0442\u0435 \u0430\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u043e process() \u0438 \u043e\u0441\u0442\u0430\u043b\u044c\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e \u043e\u0431\u0440\u0430\u0437\u0446\u0443.\n\nstatic int process_native_nhwc(int8_t *input, int *anchor, int grid_h, int grid_w,\n int height, int width, int stride,\n float_array *boxes, float_array *boxScores,\n int_array *classId,\n float threshold, int32_t zp, float scale)\n{\n int validCount = 0;\n int8_t thres_i8 = qnt_f32_to_affine(threshold, zp, scale);\n int anchor_per_branch = 3;\n int align_c = PROP_BOX_SIZE * anchor_per_branch;\n\n for (int h=0; h < grid_h; h++){\n for (int w=0; w < grid_w; w++){\n for (int a=0; a < anchor_per_branch; a++){\n int hw_offset = h * grid_w * align_c + w * align_c + a * PROP_BOX_SIZE;\n int8_t *hw_ptr = input + hw_offset;\n int8_t box_confidence = hw_ptr[4];\n if (box_confidence >= thres_i8){\n int8_t maxClassProbs = hw_ptr[5];\n int maxClassId = 0;\n for (int k = 1; k < OBJ_CLASS_NUM; ++k)\n {\n int8_t prob = hw_ptr[5 + k];\n if (prob > maxClassProbs)\n {\n maxClassId = k;\n maxClassProbs = prob;\n }\n }\n float box_conf_f32 = deqnt_affine_to_f32(box_confidence, zp, scale);\n float class_prob_f32 = deqnt_affine_to_f32(maxClassProbs, zp, scale);\n float limit_score = box_conf_f32 * class_prob_f32;\n if (limit_score > threshold){\n float box_x = deqnt_affine_to_f32(hw_ptr[0], zp, scale) * 2.0f - 0.5f;\n float box_y = deqnt_affine_to_f32(hw_ptr[1], zp, scale) * 2.0f - 0.5f;\n float box_w = deqnt_affine_to_f32(hw_ptr[2], zp, scale) * 2.0f;\n float box_h = deqnt_affine_to_f32(hw_ptr[3], zp, scale) * 2.0f;\n box_w = box_w * box_w;\n box_h = box_h * box_h;\n box_x = (box_x + w) * (float)stride;\n box_y = (box_y + h) * (float)stride;\n box_w *= (float)anchor[a * 2];\n box_h *= (float)anchor[a * 2 + 1];\n box_x -= box_w / 2.0f;\n box_y -= box_h / 2.0f;\n\n // \u0414\u043e\u0431\u0430\u0432\u043b\u044f\u0435\u043c \u0432 \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043c\u0430\u0441\u0441\u0438\u0432\u044b\n if (float_array_push(boxes, box_x) < 0) return -1;\n if (float_array_push(boxes, box_y) < 0) return -1;\n if (float_array_push(boxes, box_w) < 0) return -1;\n if (float_array_push(boxes, box_h) < 0) return -1;\n if (float_array_push(boxScores, limit_score) < 0) return -1;\n if (int_array_push(classId, maxClassId) < 0) return -1;\n\n validCount++;\n }\n }\n }\n }\n }\n return validCount;\n}\n\n// \u0410\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u043e \u043d\u0430\u043f\u0438\u0448\u0438\u0442\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 process() \u0438 \u043e\u0441\u0442\u0430\u043b\u044c\u043d\u044b\u0435...\n\n// \u041f\u0440\u0438\u043c\u0435\u0440 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 post_process\n\nint post_process(int8_t *input0, int8_t *input1, int8_t *input2,\n int model_in_h, int model_in_w,\n float conf_threshold, float nms_threshold,\n float scale_w, float scale_h,\n int32_t *qnt_zps, float *qnt_scales,\n detect_result_group_t *group)\n{\n static int init = -1;\n if (init == -1)\n {\n int ret = loadLabelName(LABEL_NALE_TXT_PATH, labels);\n if (ret < 0) return -1;\n init = 0;\n }\n\n memset(group, 0, sizeof(detect_result_group_t));\n\n // \u0418\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432\n float_array filterBoxes; float_array_init(&filterBoxes);\n float_array objProbs; float_array_init(&objProbs);\n int_array classId; int_array_init(&classId);\n\n // \u041e\u0431\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0435\u043c \u0432\u044b\u0445\u043e\u0434\u044b (stride 8,16,32)\n int grid_h, grid_w;\n int validCount0 = 0, validCount1 = 0, validCount2 = 0;\n\n grid_h = model_in_h / 8;\n grid_w = model_in_w / 8;\n validCount0 = process_native_nhwc(input0, (int *)anchor0, grid_h, grid_w,\n model_in_h, model_in_w, 8,\n &filterBoxes, &objProbs, &classId,\n conf_threshold, qnt_zps[0], qnt_scales[0]);\n\n grid_h = model_in_h / 16;\n grid_w = model_in_w / 16;\n validCount1 = process_native_nhwc(input1, (int *)anchor1, grid_h, grid_w,\n model_in_h, model_in_w, 16,\n &filterBoxes, &objProbs, &classId,\n conf_threshold, qnt_zps[1], qnt_scales[1]);\n\n grid_h = model_in_h / 32;\n grid_w = model_in_w / 32;\n validCount2 = process_native_nhwc(input2, (int *)anchor2, grid_h, grid_w,\n model_in_h, model_in_w, 32,\n &filterBoxes, &objProbs, &classId,\n conf_threshold, qnt_zps[2], qnt_scales[2]);\n\n int validCount = validCount0 + validCount1 + validCount2;\n if (validCount <= 0)\n {\n float_array_free(&filterBoxes);\n float_array_free(&objProbs);\n int_array_free(&classId);\n return 0;\n }\n\n // \u0421\u043e\u0437\u0434\u0430\u0435\u043c \u043c\u0430\u0441\u0441\u0438\u0432 \u0438\u043d\u0434\u0435\u043a\u0441\u043e\u0432 \u0434\u043b\u044f \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0438\n int *indexArray = (int *)malloc(validCount * sizeof(int));\n if (!indexArray)\n {\n float_array_free(&filterBoxes);\n float_array_free(&objProbs);\n int_array_free(&classId);\n return -1;\n }\n for (int i = 0; i < validCount; ++i)\n indexArray[i] = i;\n\n // \u0421\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430\n quick_sort_indice_inverse(&objProbs, 0, validCount - 1, indexArray);\n\n // \u0421\u043e\u0431\u0438\u0440\u0430\u0435\u043c \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0435 \u043a\u043b\u0430\u0441\u0441\u044b \u0432 \u043c\u0430\u0441\u0441\u0438\u0432\n int *unique_classes = (int *)malloc(validCount * sizeof(int));\n int unique_count = 0;\n for (int i = 0; i < validCount; ++i)\n {\n int c = classId.data[i];\n int exists = 0;\n for (int j = 0; j < unique_count; ++j)\n if (unique_classes[j] == c) {\n exists = 1;\n break;\n }\n if (!exists)\n unique_classes[unique_count++] = c;\n }\n\n // NMS \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043a\u043b\u0430\u0441\u0441\u0430\n for (int cidx = 0; cidx < unique_count; ++cidx)\n {\n nms(validCount, &filterBoxes, &classId, indexArray, unique_classes[cidx], nms_threshold);\n }\n free(unique_classes);\n\n int last_count = 0;\n group->count = 0;\n // \u041a\u043e\u043f\u0438\u0440\u0443\u0435\u043c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b\n for (int i = 0; i < validCount; ++i)\n {\n int idx = indexArray[i];\n if (idx == -1 || last_count >= OBJ_NUMB_MAX_SIZE)\n continue;\n\n float x1 = filterBoxes.data[idx * 4 + 0];\n float y1 = filterBoxes.data[idx * 4 + 1];\n float x2 = x1 + filterBoxes.data[idx * 4 + 2];\n float y2 = y1 + filterBoxes.data[idx * 4 + 3];\n int id = classId.data[idx];\n float obj_conf = objProbs.data[i];\n\n group->results[last_count].box.left = clamp_i(x1 / scale_w, 0, model_in_w);\n group->results[last_count].box.top = clamp_i(y1 / scale_h, 0, model_in_h);\n group->results[last_count].box.right = clamp_i(x2 / scale_w, 0, model_in_w);\n group->results[last_count].box.bottom = clamp_i(y2 / scale_h, 0, model_in_h);\n group->results[last_count].prop = obj_conf;\n if (id >= 0 && id < OBJ_CLASS_NUM && labels[id])\n strncpy(group->results[last_count].name, labels[id], OBJ_NAME_MAX_SIZE - 1);\n group->results[last_count].name[OBJ_NAME_MAX_SIZE-1] = 0;\n\n last_count++;\n }\n group->count = last_count;\n\n free(indexArray);\n float_array_free(&filterBoxes);\n float_array_free(&objProbs);\n int_array_free(&classId);\n\n return 0;\n}\n```\n\n---\n\n### \u041f\u043e\u044f\u0441\u043d\u0435\u043d\u0438\u044f:\n\n- \u0417\u0430\u043c\u0435\u043d\u0438\u043b\u0438 `std::vector` \u043d\u0430 `float_array` \u0438 `int_array` \u2014 \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043c\u0430\u0441\u0441\u0438\u0432\u044b \u0441 \u0434\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0435\u043c/\u0443\u0434\u0430\u043b\u0435\u043d\u0438\u0435\u043c.\n- \u0412\u043c\u0435\u0441\u0442\u043e `std::set` \u2014 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u043d\u0430\u0438\u0432\u043d\u044b\u0439 \u043f\u043e\u0438\u0441\u043a \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u044d\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u0432 \u0432 \u043c\u0430\u0441\u0441\u0438\u0432\u0435.\n- \u0412\u043c\u0435\u0441\u0442\u043e `for(auto c : class_set)` \u2014 \u0438\u0442\u0435\u0440\u0430\u0446\u0438\u044f \u043f\u043e \u043c\u0430\u0441\u0441\u0438\u0432\u0443 \u0443\u043d\u0438\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u043a\u043b\u0430\u0441\u0441\u043e\u0432.\n- \u0414\u043e\u0431\u0430\u0432\u043b\u0435\u043d \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044c \u043e\u0448\u0438\u0431\u043e\u043a \u043f\u0440\u0438 malloc/realloc.\n- \u0421\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u044b\u0435 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u0447\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 `malloc`, `realloc`, `free`, `memset`, `strncpy` \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442\u0441\u044f \u043a\u0430\u043a \u0435\u0441\u0442\u044c.\n- \u041d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u043e \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c `loadLabelName` \u0438 `readLine` \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e(\u0432\u044b\u0448\u0435 \u0432\u0430\u0448 \u043a\u043e\u0434 \u0443\u0436\u0435 \u043d\u0430 \u0447\u0438\u0441\u0442\u043e\u043c C).\n- \u0423\u0431\u0435\u0434\u0438\u0442\u0435\u0441\u044c, \u0447\u0442\u043e \u043c\u0430\u0441\u0441\u0438\u0432\u044b `labels[]`, `anchor0`, `anchor1`, `anchor2` \u043e\u0431\u044a\u044f\u0432\u043b\u0435\u043d\u044b \u0433\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u043e \u0438 \u0432\u0438\u0434\u043d\u044b.\n- \u041f\u0440\u043e\u0432\u0435\u0440\u044c\u0442\u0435 \u0447\u0442\u043e `PROP_BOX_SIZE`, `OBJ_CLASS_NUM`, `OBJ_NUMB_MAX_SIZE`, `OBJ_NAME_MAX_SIZE` \u043e\u0431\u044a\u044f\u0432\u043b\u0435\u043d\u044b \u0438 \u0438\u043c\u0435\u044e\u0442 \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f.\n- \u0424\u0443\u043d\u043a\u0446\u0438\u0438 `process()` \u0438 `process_native_nhwc()` \u043c\u043e\u0436\u043d\u043e \u043f\u0440\u0438\u0432\u0435\u0441\u0442\u0438 \u0432 \u0430\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u044b\u0439 \u0441\u0442\u0438\u043b\u044c.\n\n---\n\n\u0415\u0441\u043b\u0438 \u043d\u0443\u0436\u043d\u043e \u2014 \u043c\u043e\u0433\u0443 \u043f\u043e\u043c\u043e\u0447\u044c \u0441 \u0434\u043e\u0440\u0430\u0431\u043e\u0442\u043a\u043e\u0439 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u044b\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439. \n\u042d\u0442\u043e \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e\u0435 \u0438 \u0440\u0430\u0431\u043e\u0447\u0435\u0435 \u043d\u0430\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u043f\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0432\u0430\u0448\u0435\u0433\u043e C++ \u043a\u043e\u0434\u0430 \u0432 \u0447\u0438\u0441\u0442\u044b\u0439 C \u0441 \u043c\u0438\u043d\u0438\u043c\u0430\u043b\u044c\u043d\u043e \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b\u043c\u0438 \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u044f\u043c\u0438 \u043f\u043e\u0434 \u043e\u0442\u0441\u0443\u0442\u0441\u0442\u0432\u0438\u0435 STL.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":30678,"n_turns_in_conversation":10,"n_words":3490,"source_row_offset":23308,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"be061353a0193c0c405d12c9","turn_index":3,"user_text":"\u0422\u0435\u043f\u0435\u0440\u044c \u0442\u0443\u0442 \u043d\u0430 \u0447\u0438\u0441\u0442\u043e\u043c \u0421\u0418 \n// Copyright (c) 2021 by Rockchip Electronics Co., Ltd. All Rights Reserved.\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// http://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \"postprocess.h\"\n#include \n#define LABEL_NALE_TXT_PATH \"./model/coco_80_labels_list.txt\"\n\nstatic char *labels[OBJ_CLASS_NUM];\n\nconst int anchor0[6] = {10, 13, 16, 30, 33, 23};\nconst int anchor1[6] = {30, 61, 62, 45, 59, 119};\nconst int anchor2[6] = {116, 90, 156, 198, 373, 326};\n\ninline static int clamp(float val, int min, int max)\n{\n return val > min ? (val < max ? val : max) : min;\n}\n\nchar *readLine(FILE *fp, char *buffer, int *len)\n{\n int ch;\n int i = 0;\n size_t buff_len = 0;\n\n buffer = (char *)malloc(buff_len + 1);\n if (!buffer)\n return NULL; // Out of memory\n\n while ((ch = fgetc(fp)) != '\\n' && ch != EOF)\n {\n buff_len++;\n void *tmp = realloc(buffer, buff_len + 1);\n if (tmp == NULL)\n {\n free(buffer);\n return NULL; // Out of memory\n }\n buffer = (char *)tmp;\n\n buffer[i] = (char)ch;\n i++;\n }\n buffer[i] = '\\0';\n\n *len = buff_len;\n\n // Detect end\n if (ch == EOF && (i == 0 || ferror(fp)))\n {\n free(buffer);\n return NULL;\n }\n return buffer;\n}\n\nint readLines(const char *fileName, char *lines[], int max_line)\n{\n FILE *file = fopen(fileName, \"r\");\n char *s;\n int i = 0;\n int n = 0;\n while ((s = readLine(file, s, &n)) != NULL)\n {\n lines[i++] = s;\n if (i >= max_line)\n break;\n }\n return i;\n}\n\nint loadLabelName(const char *locationFilename, char *label[])\n{\n printf(\"loadLabelName %s\\n\", locationFilename);\n readLines(locationFilename, label, OBJ_CLASS_NUM);\n return 0;\n}\n\nstatic float CalculateOverlap(float xmin0, float ymin0, float xmax0, float ymax0, float xmin1, float ymin1, float xmax1, float ymax1)\n{\n float w = fmax(0.f, fmin(xmax0, xmax1) - fmax(xmin0, xmin1) + 1.0);\n float h = fmax(0.f, fmin(ymax0, ymax1) - fmax(ymin0, ymin1) + 1.0);\n float i = w * h;\n float u = (xmax0 - xmin0 + 1.0) * (ymax0 - ymin0 + 1.0) + (xmax1 - xmin1 + 1.0) * (ymax1 - ymin1 + 1.0) - i;\n return u <= 0.f ? 0.f : (i / u);\n}\n\nstatic int nms(int validCount, std::vector &outputLocations, std::vector classIds, std::vector &order,int filterId, float threshold)\n{\n for (int i = 0; i < validCount; ++i)\n {\n if (order[i] == -1|| classIds[i] != filterId)\n {\n continue;\n }\n int n = order[i];\n for (int j = i + 1; j < validCount; ++j)\n {\n int m = order[j];\n if (m == -1 || classIds[i] != filterId)\n {\n continue;\n }\n float xmin0 = outputLocations[n * 4 + 0];\n float ymin0 = outputLocations[n * 4 + 1];\n float xmax0 = outputLocations[n * 4 + 0] + outputLocations[n * 4 + 2];\n float ymax0 = outputLocations[n * 4 + 1] + outputLocations[n * 4 + 3];\n\n float xmin1 = outputLocations[m * 4 + 0];\n float ymin1 = outputLocations[m * 4 + 1];\n float xmax1 = outputLocations[m * 4 + 0] + outputLocations[m * 4 + 2];\n float ymax1 = outputLocations[m * 4 + 1] + outputLocations[m * 4 + 3];\n\n float iou = CalculateOverlap(xmin0, ymin0, xmax0, ymax0, xmin1, ymin1, xmax1, ymax1);\n\n if (iou > threshold)\n {\n order[j] = -1;\n }\n }\n }\n return 0;\n}\n\nstatic int quick_sort_indice_inverse(\n std::vector &input,\n int left,\n int right,\n std::vector &indices)\n{\n float key;\n int key_index;\n int low = left;\n int high = right;\n if (left < right)\n {\n key_index = indices[left];\n key = input[left];\n while (low < high)\n {\n while (low < high && input[high] <= key)\n {\n high--;\n }\n input[low] = input[high];\n indices[low] = indices[high];\n while (low < high && input[low] >= key)\n {\n low++;\n }\n input[high] = input[low];\n indices[high] = indices[low];\n }\n input[low] = key;\n indices[low] = key_index;\n quick_sort_indice_inverse(input, left, low - 1, indices);\n quick_sort_indice_inverse(input, low + 1, right, indices);\n }\n return low;\n}\n\nstatic float sigmoid(float x)\n{\n return 1.0 / (1.0 + expf(-x));\n}\n\nstatic float unsigmoid(float y)\n{\n return -1.0 * logf((1.0 / y) - 1.0);\n}\n\ninline static int32_t __clip(float val, float min, float max)\n{\n float f = val <= min ? min : (val >= max ? max : val);\n return f;\n}\n\nstatic int8_t qnt_f32_to_affine(float f32, int32_t zp, float scale)\n{\n float dst_val = (f32 / scale) + zp;\n int8_t res = (int8_t)__clip(dst_val, -128, 127);\n return res;\n}\n\nstatic float deqnt_affine_to_f32(int8_t qnt, int32_t zp, float scale)\n{\n return ((float)qnt - (float)zp) * scale;\n}\n\nstatic int process(int8_t *input, int *anchor, int grid_h, int grid_w, int height, int width, int stride,\n std::vector &boxes, std::vector &objProbs, std::vector &classId,\n float threshold, int32_t zp, float scale)\n{\n\n int validCount = 0;\n int grid_len = grid_h * grid_w;\n int8_t thres_i8 = qnt_f32_to_affine(threshold, zp, scale);\n for (int a = 0; a < 3; a++)\n {\n for (int i = 0; i < grid_h; i++)\n {\n for (int j = 0; j < grid_w; j++)\n {\n int8_t box_confidence = input[(PROP_BOX_SIZE * a + 4) * grid_len + i * grid_w + j];\n if (box_confidence >= thres_i8)\n {\n int offset = (PROP_BOX_SIZE * a) * grid_len + i * grid_w + j;\n int8_t *in_ptr = input + offset;\n float box_x = (deqnt_affine_to_f32(*in_ptr, zp, scale)) * 2.0 - 0.5;\n float box_y = (deqnt_affine_to_f32(in_ptr[grid_len], zp, scale)) * 2.0 - 0.5;\n float box_w = (deqnt_affine_to_f32(in_ptr[2 * grid_len], zp, scale)) * 2.0;\n float box_h = (deqnt_affine_to_f32(in_ptr[3 * grid_len], zp, scale)) * 2.0;\n box_x = (box_x + j) * (float)stride;\n box_y = (box_y + i) * (float)stride;\n box_w = box_w * box_w * (float)anchor[a * 2];\n box_h = box_h * box_h * (float)anchor[a * 2 + 1];\n box_x -= (box_w / 2.0);\n box_y -= (box_h / 2.0);\n\n int8_t maxClassProbs = in_ptr[5 * grid_len];\n int maxClassId = 0;\n for (int k = 1; k < OBJ_CLASS_NUM; ++k)\n {\n int8_t prob = in_ptr[(5 + k) * grid_len];\n if (prob > maxClassProbs)\n {\n maxClassId = k;\n maxClassProbs = prob;\n }\n }\n if (maxClassProbs>thres_i8){\n boxes.push_back(box_x);\n boxes.push_back(box_y);\n boxes.push_back(box_w);\n boxes.push_back(box_h);\n objProbs.push_back((deqnt_affine_to_f32(maxClassProbs, zp, scale))* (deqnt_affine_to_f32(box_confidence, zp, scale)));\n classId.push_back(maxClassId);\n validCount++;\n }\n }\n }\n }\n }\n return validCount;\n}\n\n\nstatic int process_native_nhwc(int8_t *input, int *anchor, int grid_h, int grid_w, int height, int width, int stride,\n std::vector &boxes, std::vector &boxScores, std::vector &classId,\n float threshold, int32_t zp, float scale)\n{\n int validCount = 0;\n int8_t thres_i8 = qnt_f32_to_affine(threshold, zp, scale);\n\n int anchor_per_branch = 3;\n // \u65b0\u9a71\u52a8\u4e0d\u518d\u6709\u5bf9\u9f50\u8981\u6c42\n // int align_c = get_align(PROP_BOX_SIZE*anchor_per_branch, 16);\n int align_c = PROP_BOX_SIZE*anchor_per_branch;\n // printf(\"align_c %d\\n\", align_c);\n\n for (int h=0; h < grid_h; h++){\n for (int w=0; w < grid_w; w++){\n for (int a=0; a < anchor_per_branch; a++){\n int hw_offset = h*grid_w*align_c + w*align_c + a*PROP_BOX_SIZE;\n // int hw_offset = h*grid_w*anchor_per_branch*PROP_BOX_SIZE + w*anchor_per_branch*PROP_BOX_SIZE + a*PROP_BOX_SIZE;\n int8_t *hw_ptr = input + hw_offset;\n int8_t box_confidence = hw_ptr[4];\n \n if (box_confidence >= thres_i8){\n // printf(\"box_conf %d, thres_i8 %d\\n\", box_confidence, thres_i8);\n\n int8_t maxClassProbs = hw_ptr[5];\n int maxClassId = 0;\n for (int k = 1; k < OBJ_CLASS_NUM; ++k)\n {\n int8_t prob = hw_ptr[5 + k];\n if (prob > maxClassProbs)\n {\n maxClassId = k;\n maxClassProbs = prob;\n }\n }\n\n // printf(\"box_conf %d, thres_i8 %d, maxClassProbs %d\\n\", box_confidence, thres_i8, maxClassProbs);\n float box_conf_f32 = deqnt_affine_to_f32(box_confidence, zp, scale);\n float class_prob_f32 = deqnt_affine_to_f32(maxClassProbs, zp, scale);\n float limit_score = box_conf_f32* class_prob_f32;\n\n if (limit_score > threshold){\n float box_x, box_y, box_w, box_h;\n\n box_x = deqnt_affine_to_f32(hw_ptr[0], zp, scale) * 2.0 - 0.5;\n box_y = deqnt_affine_to_f32(hw_ptr[1], zp, scale) * 2.0 - 0.5;\n box_w = deqnt_affine_to_f32(hw_ptr[2], zp, scale) * 2.0;\n box_h = deqnt_affine_to_f32(hw_ptr[3], zp, scale) * 2.0;\n box_w = box_w * box_w;\n box_h = box_h * box_h;\n\n\n box_x = (box_x + w) * (float)stride;\n box_y = (box_y + h) * (float)stride;\n box_w *= (float)anchor[a * 2];\n box_h *= (float)anchor[a * 2 + 1];\n\n box_x -= (box_w / 2.0);\n box_y -= (box_h / 2.0);\n\n boxes.push_back(box_x);\n boxes.push_back(box_y);\n boxes.push_back(box_w);\n boxes.push_back(box_h);\n boxScores.push_back(limit_score);\n classId.push_back(maxClassId);\n validCount++;\n }\n }\n }\n }\n }\n return validCount;\n}\n\nint post_process(int8_t *input0, int8_t *input1, int8_t *input2, int model_in_h, int model_in_w,\n float conf_threshold, float nms_threshold, float scale_w, float scale_h,\n std::vector &qnt_zps, std::vector &qnt_scales,\n detect_result_group_t *group)\n{\n static int init = -1;\n if (init == -1)\n {\n int ret = 0;\n ret = loadLabelName(LABEL_NALE_TXT_PATH, labels);\n if (ret < 0)\n {\n return -1;\n }\n\n init = 0;\n }\n memset(group, 0, sizeof(detect_result_group_t));\n\n std::vector filterBoxes;\n std::vector objProbs;\n std::vector classId;\n \n // stride 8\n int stride0 = 8;\n int grid_h0 = model_in_h / stride0;\n int grid_w0 = model_in_w / stride0;\n int validCount0 = 0;\n validCount0 = process_native_nhwc(input0, (int *)anchor0, grid_h0, grid_w0, model_in_h, model_in_w,\n stride0, filterBoxes, objProbs, classId, conf_threshold, qnt_zps[0], qnt_scales[0]);\n\n // stride 16\n int stride1 = 16;\n int grid_h1 = model_in_h / stride1;\n int grid_w1 = model_in_w / stride1;\n int validCount1 = 0;\n validCount1 = process_native_nhwc(input1, (int *)anchor1, grid_h1, grid_w1, model_in_h, model_in_w,\n stride1, filterBoxes, objProbs, classId, conf_threshold, qnt_zps[1], qnt_scales[1]);\n\n // stride 32\n int stride2 = 32;\n int grid_h2 = model_in_h / stride2;\n int grid_w2 = model_in_w / stride2;\n int validCount2 = 0;\n validCount2 = process_native_nhwc(input2, (int *)anchor2, grid_h2, grid_w2, model_in_h, model_in_w,\n stride2, filterBoxes, objProbs, classId, conf_threshold, qnt_zps[2], qnt_scales[2]);\n\n int validCount = validCount0 + validCount1 + validCount2;\n // no object detect\n if (validCount <= 0)\n {\n return 0;\n }\n\n std::vector indexArray;\n for (int i = 0; i < validCount; ++i)\n {\n indexArray.push_back(i);\n }\n\n quick_sort_indice_inverse(objProbs, 0, validCount - 1, indexArray);\n\n std::set class_set(std::begin(classId),std::end(classId));\n \n for(auto c : class_set){\n nms(validCount, filterBoxes, classId, indexArray, c, nms_threshold);\n }\n\n int last_count = 0;\n group->count = 0;\n /* box valid detect target */\n for (int i = 0; i < validCount; ++i)\n {\n\n if (indexArray[i] == -1 || last_count >= OBJ_NUMB_MAX_SIZE)\n {\n continue;\n }\n int n = indexArray[i];\n\n float x1 = filterBoxes[n * 4 + 0];\n float y1 = filterBoxes[n * 4 + 1];\n float x2 = x1 + filterBoxes[n * 4 + 2];\n float y2 = y1 + filterBoxes[n * 4 + 3];\n int id = classId[n];\n float obj_conf = objProbs[i];\n\n group->results[last_count].box.left = (int)(clamp(x1, 0, model_in_w) / scale_w);\n group->results[last_count].box.top = (int)(clamp(y1, 0, model_in_h) / scale_h);\n group->results[last_count].box.right = (int)(clamp(x2, 0, model_in_w) / scale_w);\n group->results[last_count].box.bottom = (int)(clamp(y2, 0, model_in_h) / scale_h);\n group->results[last_count].prop = obj_conf;\n char *label = labels[id];\n strncpy(group->results[last_count].name, label, OBJ_NAME_MAX_SIZE);\n\n // printf(\"result %2d: (%4d, %4d, %4d, %4d), %s\\n\", i, group->results[last_count].box.left, group->results[last_count].box.top,\n // group->results[last_count].box.right, group->results[last_count].box.bottom, label);\n last_count++;\n }\n group->count = last_count;\n\n return 0;\n}\n"},{"assistant_initiates":false,"asst_text":"\u042d\u0442\u043e \u0441\u043e\u043e\u0431\u0449\u0435\u043d\u0438\u044f \u043e\u0442 ffmpeg \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 (libavformat) \u043e\u0431 \u043e\u0448\u0438\u0431\u043a\u0430\u0445 RTSP \u2014 warnings \u0438 info, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0432\u044b\u0432\u043e\u0434\u044f\u0442\u0441\u044f \u0432 stderr \u0447\u0435\u0440\u0435\u0437 \u0432\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u0438\u0439 \u043b\u043e\u0433\u0433\u0435\u0440.\n\n\u0427\u0442\u043e\u0431\u044b \u0438\u0445 \u043f\u043e\u0434\u0430\u0432\u0438\u0442\u044c \u0438\u043b\u0438 \u043e\u0442\u043a\u043b\u044e\u0447\u0438\u0442\u044c, \u0435\u0441\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u043f\u043e\u0441\u043e\u0431\u043e\u0432:\n\n---\n\n### \u0421\u043f\u043e\u0441\u043e\u0431 1. \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u043b\u043e\u0433\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f FFmpeg \u0432 \u043a\u043e\u0434\u0435\n\n\u0412 \u043d\u0430\u0447\u0430\u043b\u0435 \u0432\u0430\u0448\u0435\u0439 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u044b (\u043f\u043e\u0441\u043b\u0435 \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 ffmpeg, \u043e\u0431\u044b\u0447\u043d\u043e \u0441\u0440\u0430\u0437\u0443 \u043f\u043e\u0441\u043b\u0435 `avformat_network_init()`) \u0434\u043e\u0431\u0430\u0432\u044c\u0442\u0435\n\n```c\nav_log_set_level(AV_LOG_QUIET); // \u041f\u043e\u043b\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435 \u0432\u044b\u0432\u043e\u0434\u0430 \u043b\u043e\u0433\u043e\u0432 ffmpeg\n```\n\n\u0418\u043b\u0438 \u0431\u043e\u043b\u0435\u0435 \u043c\u044f\u0433\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, WARN \u0438\u043b\u0438 ERROR):\n\n```c\nav_log_set_level(AV_LOG_ERROR);\n```\n\n\u0427\u0435\u043c \u0432\u044b\u0448\u0435 \u0443\u0440\u043e\u0432\u0435\u043d\u044c, \u0442\u0435\u043c \u043c\u0435\u043d\u044c\u0448\u0435 \u043b\u043e\u0433\u043e\u0432.\n\n---\n\n### \u0421\u043f\u043e\u0441\u043e\u0431 2. \u0423\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c \u0441\u043e\u0431\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0439 \u043b\u043e\u0433-\u0444\u0443\u043d\u043a\u0446\u0438\u044e, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u043d\u0438\u0447\u0435\u0433\u043e \u043d\u0435 \u0432\u044b\u0432\u043e\u0434\u0438\u0442\n\n```c\nvoid null_log_callback(void* ptr, int level, const char* fmt, va_list vl) {\n // \u041d\u0438\u0447\u0435\u0433\u043e \u043d\u0435 \u0434\u0435\u043b\u0430\u0435\u043c \u2014 \u043b\u043e\u0433 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u0443\u0435\u043c\n}\n\nint main()\n{\n av_log_set_callback(null_log_callback);\n // \u0434\u0430\u043b\u0435\u0435 \u0432\u0430\u0448\u0430 \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0438 \u043a\u043e\u0434\n}\n```\n\n---\n\n### \u0421\u043f\u043e\u0441\u043e\u0431 3. \u041e\u0431\u044b\u0447\u043d\u043e \u0432 \u043a\u043e\u043c\u0430\u043d\u0434\u0435 ffmpeg CLI \u0438\u043b\u0438 \u043f\u0440\u0438 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0435 AVFormatContext \u043c\u043e\u0436\u043d\u043e \u0437\u0430\u0434\u0430\u0442\u044c \u043e\u043f\u0446\u0438\u044e `-loglevel quiet` \u2014 \u0432 API \u044d\u0442\u043e \u0447\u0435\u0440\u0435\u0437 `av_log_set_level()`.\n\n---\n\n### \u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435\n\n\u0414\u043b\u044f \u0432\u0430\u0448\u0435\u0433\u043e \u0441\u043b\u0443\u0447\u0430\u044f \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e \u0432\u044b\u0437\u043e\u0432\u0430\n\n```c\nav_log_set_level(AV_LOG_ERROR);\n```\n\n\u0447\u0442\u043e\u0431\u044b \u0441\u043a\u0440\u044b\u0442\u044c \u043f\u0440\u0435\u0434\u0443\u043f\u0440\u0435\u0436\u0434\u0435\u043d\u0438\u044f \u0442\u0438\u043f\u0430 \"[rtsp @ 0x25a10] CSeq ... expected ... received\" \u0438 \u0432\u044b\u0432\u043e\u0434\u0438\u0442\u044c \u0442\u043e\u043b\u044c\u043a\u043e \u043e\u0448\u0438\u0431\u043a\u0438 (\u0438\u043b\u0438 AV_LOG_QUIET, \u0435\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u043f\u043e\u043b\u043d\u043e\u0441\u0442\u044c\u044e).\n\n---\n\n### \u041f\u0440\u0438\u043c\u0435\u0440 \u0432 \u043a\u043e\u0434\u0435\n\n```c\nint main(int argc, char *argv[]) {\n avformat_network_init();\n\n av_log_set_level(AV_LOG_ERROR);\n\n // \u0432\u0430\u0448 \u043e\u0441\u0442\u0430\u043b\u044c\u043d\u043e\u0439 \u043a\u043e\u0434\n}\n```\n\n---\n\n\u0415\u0441\u043b\u0438 \u043b\u043e\u0433 \u043d\u0443\u0436\u043d\u043e \u00ab\u043f\u0435\u0440\u0435\u043a\u043b\u044e\u0447\u0430\u0442\u044c\u00bb \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u0438 \u2014 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0439\u0442\u0435 `av_log_set_level()`.\n\n---\n\n\u0415\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u043f\u043e\u0434\u0430\u0432\u0438\u0442\u044c \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u044b\u0435 \u0441\u043e\u043e\u0431\u0449\u0435\u043d\u0438\u044f, \u043d\u043e \u043e\u0441\u0442\u0430\u0432\u0438\u0442\u044c \u043e\u0441\u0442\u0430\u043b\u044c\u043d\u044b\u0435 \u2014 \u043f\u0440\u0438\u0434\u0435\u0442\u0441\u044f \u043f\u0438\u0441\u0430\u0442\u044c \u043a\u0430\u0441\u0442\u043e\u043c\u043d\u0443\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u044e \u043b\u043e\u0433\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u0444\u0438\u043b\u044c\u0442\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u0441\u043e\u043e\u0431\u0449\u0435\u043d\u0438\u044e (\u0432 `av_log_set_callback()`).\n\n---\n\n\u0415\u0441\u043b\u0438 \u043d\u0443\u0436\u043d\u0430 \u043f\u043e\u043c\u043e\u0449\u044c \u2014 \u043f\u0438\u0448\u0438\u0442\u0435!","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":2315,"n_turns_in_conversation":10,"n_words":320,"source_row_offset":23309,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"24e64e9b3730e235c304e49a","turn_index":4,"user_text":"\u043a\u0430\u043a \u0443\u0431\u0440\u0430\u0442\u044c \u0432\u044b\u0432\u043e\u0434 x25a10] CSeq 312 expected, 301 received.\n[rtsp @ 0x25a10] CSeq 312 expected, 302 received.\n[rtsp @ 0x25a10] CSeq 312 expected, 307 received.\n[rtsp @ 0x25a10] CSeq 312 expected, 311 received.\n[rtsp @ 0x25a10] CSeq 322 expected, 313 received.\n[rtsp @ 0x25a10] CSeq 322 expected, 314 received.\n[rtsp @ 0x25a10] CSeq 322 expected, 318 received.\n[rtsp @ 0x25a10] CSeq 331 expected, 323 received.\n[rtsp @ 0x25a10] CSeq 331 expected, 324 received.\n[rtsp @ 0x25a10] CSeq 331 expected, 329 received.\n[rtsp @ 0x25a10] CSeq 343 expected, 332 receiv"},{"assistant_initiates":false,"asst_text":"\u0415\u0441\u043b\u0438 \u043c\u043e\u0434\u0435\u043b\u044c \u043e\u0436\u0438\u0434\u0430\u0435\u0442 \u043a\u0430\u0434\u0440 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u0433\u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0430 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, 640x640) \u0438 \u043f\u0438\u043a\u0441\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u0444\u043e\u0440\u043c\u0430\u0442\u0430 (\u0447\u0430\u0449\u0435 RGB24 \u0432 \u0432\u0430\u0448\u0435\u043c \u0441\u043b\u0443\u0447\u0430\u0435), \u0430 `frame` \u0443 \u0432\u0430\u0441 \u0438\u0437 \u0434\u0435\u043a\u043e\u0434\u0435\u0440\u0430 \u2014 \u043e\u0431\u044b\u0447\u043d\u043e \u0432 \u0444\u043e\u0440\u043c\u0430\u0442\u0435 YUV (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, YUV420P) \u0438 \u0434\u0440\u0443\u0433\u043e\u043c \u0440\u0430\u0437\u0440\u0435\u0448\u0435\u043d\u0438\u0438, \u0442\u043e:\n\n---\n\n### \u0417\u0430\u0447\u0435\u043c \u043d\u0443\u0436\u0435\u043d `sws_scale`?\n\n`avcodec_receive_frame()` \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u043a\u0430\u0434\u0440 \u0432 \u0444\u043e\u0440\u043c\u0430\u0442\u0435 \u0441\u044b\u0440\u043e\u0433\u043e \u0432\u0438\u0434\u0435\u043e (\u0447\u0430\u0449\u0435 YUV).\n\n\u041c\u043e\u0434\u0435\u043b\u044c RKNN \u043e\u0431\u044b\u0447\u043d\u043e \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0435\u0442 RGB24 (\u0438\u043b\u0438 \u0434\u0440\u0443\u0433\u043e\u0439), \u0438 \u0441\u0442\u0440\u043e\u0433\u043e \u0444\u0438\u043a\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0440\u0430\u0437\u043c\u0435\u0440.\n\n`rgb_frame` \u2014 \u044d\u0442\u043e \u0432\u044b\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0439 \u043f\u043e\u0434 RGB \u043a\u0430\u0434\u0440\u043e\u0432\u044b\u0439 \u0431\u0443\u0444\u0435\u0440 \u043d\u0443\u0436\u043d\u043e\u0433\u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0430.\n\n`sws_scale()` \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0438\u0440\u0443\u0435\u0442 \u0438 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0438\u0440\u0443\u0435\u0442 \u0438\u0437 \u0438\u0441\u0445\u043e\u0434\u043d\u043e\u0433\u043e \u0444\u043e\u0440\u043c\u0430\u0442\u0430 (YUV + \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b\u044c\u043d\u044b\u0439 \u0440\u0430\u0437\u043c\u0435\u0440) \u2192 RGB24 + \u043d\u0443\u0436\u043d\u044b\u0439 \u0440\u0430\u0437\u043c\u0435\u0440.\n\n\u041f\u043e\u0441\u043b\u0435 \u0447\u0435\u0433\u043e `rgb_frame` \u0433\u043e\u0442\u043e\u0432 \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0438 \u0432 RKNN.\n\n---\n\n### \u041c\u043e\u0436\u043d\u043e \u043b\u0438 \u043f\u0435\u0440\u0435\u0434\u0430\u0442\u044c \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e \u0438\u0437 `frame->data` \u0432 `resize_and_copy_frame_to_input`?\n\n\u041d\u0435\u0442, **\u043d\u0435\u043b\u044c\u0437\u044f**, \u043f\u043e\u0442\u043e\u043c\u0443 \u0447\u0442\u043e:\n\n- `frame->data` \u2014 \u0432 YUV \u0444\u043e\u0440\u043c\u0430\u0442\u0435, \u041d\u0415 RGB.\n\n- `frame->data` \u043c\u043e\u0433 \u0438\u043c\u0435\u0442\u044c \u043b\u044e\u0431\u043e\u0439 \u0440\u0430\u0437\u043c\u0435\u0440 \u0438 \u0444\u043e\u0440\u043c\u0430\u0442, \u043e\u0442\u043b\u0438\u0447\u0430\u044e\u0449\u0438\u0439\u0441\u044f \u043e\u0442 \u043c\u043e\u0434\u0435\u043b\u0438.\n\n---\n\n### \u041c\u043e\u0436\u043d\u043e \u043b\u0438 \u043d\u0435 \u0434\u0435\u043b\u0430\u0442\u044c `resize_and_copy_frame_to_input` \u0438 \u043f\u0435\u0440\u0435\u0434\u0430\u0432\u0430\u0442\u044c `rgb_frame->data` \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e?\n\n- **\u041c\u043e\u0436\u043d\u043e**, \u0435\u0441\u043b\u0438:\n\n - \u0412\u0430\u0448\u0430 \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0435\u0442 \u0432\u0445\u043e\u0434 \u0441\u0442\u0440\u043e\u0433\u043e \u0432 \u0444\u043e\u0440\u043c\u0430\u0442\u0435 \u0438 \u0440\u0430\u0437\u043c\u0435\u0440\u0435, \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0435\u043c `rgb_frame`.\n\n - \u041f\u0440\u0438 \u044d\u0442\u043e\u043c \u0432\u044b \u0443\u043a\u0430\u0436\u0435\u0442\u0435 RKNN \u043d\u0443\u0436\u043d\u044b\u0439 \u0444\u043e\u0440\u043c\u0430\u0442 \u0438 \u0440\u0430\u0437\u043c\u0435\u0440.\n\n- `resize_and_copy_frame_to_input()` \u043e\u0431\u044b\u0447\u043d\u043e \u0434\u0435\u043b\u0430\u0435\u0442 \u0442\u043e\u043b\u044c\u043a\u043e \u043a\u043e\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0438\u0437 `rgb_frame->data` (\u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0443\u0436\u0435 640x640 RGB) \u0432 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u044b\u0439 \u0431\u0443\u0444\u0435\u0440 RKNN \u0432\u0445\u043e\u0434\u0430.\n\n\u0415\u0441\u043b\u0438 `rgb_frame->data` \u0438 RKNN \u0432\u0445\u043e\u0434 (input_mem) \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0442 \u043f\u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0443, \u0444\u043e\u0440\u043c\u0430\u0442\u0443 \u0438 \u043f\u0430\u043c\u044f\u0442\u0438 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, zero-copy), \u0442\u043e \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u043f\u0440\u043e\u0431\u043e\u0432\u0430\u0442\u044c \u043f\u0435\u0440\u0435\u0434\u0430\u0432\u0430\u0442\u044c \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e \u0438\u043b\u0438 \u0443\u043a\u0430\u0437\u0430\u0442\u044c RKNN \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u043e\u0442 \u0431\u0443\u0444\u0435\u0440.\n\n---\n\n### \u0415\u0441\u043b\u0438 `resize_and_copy_frame_to_input` \u0442\u043e\u043b\u044c\u043a\u043e \u043a\u043e\u043f\u0438\u0440\u0443\u0435\u0442 \u0438 \u043d\u0435 \u0434\u0435\u043b\u0430\u0435\u0442 \u0440\u0435\u0441\u0430\u0439\u0437\u0430\n\n\u042d\u0442\u043e \u043d\u043e\u0440\u043c\u0430\u043b\u044c\u043d\u043e \u2014 \u0440\u0435\u0441\u0430\u0439\u0437 \u0438 \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0430\u0446\u0438\u044f \u0434\u0435\u043b\u0430\u0435\u0442\u0441\u044f **\u043e\u0434\u0438\u043d \u0440\u0430\u0437 \u0432 `sws_scale`**, \u0430 \u043a\u043e\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u2014 \u0447\u0442\u043e\u0431\u044b \u043f\u043e\u043b\u043e\u0436\u0438\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 \u0432\u044b\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0439 \u0434\u043b\u044f RKNN \u0431\u0443\u0444\u0435\u0440.\n\n---\n\n### \u0412\u044b\u0432\u043e\u0434:\n\n- `sws_scale` \u2014 **\u043e\u0431\u044f\u0437\u0430\u0442\u0435\u043b\u0435\u043d** \u0434\u043b\u044f \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0430\u0446\u0438\u0438 \u0438\u0437 \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u0432\u0438\u0434\u0435\u043e\u043a\u0430\u0434\u0440\u0430 (YUV) \u0432 RGB \u043d\u0443\u0436\u043d\u043e\u0433\u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0430.\n\n- `resize_and_copy_frame_to_input` \u2014 \u0434\u043b\u044f \u043a\u043e\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f RGB \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 \u0431\u0443\u0444\u0435\u0440 RKNN.\n\n\u041c\u043e\u0436\u043d\u043e \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c, \u0435\u0441\u043b\u0438:\n\n- \u0412\u044b\u0434\u0435\u043b\u0438\u0442\u044c \u0431\u0443\u0444\u0435\u0440 `rgb_frame` \u0442\u0430\u043a\u0438\u043c\u0438 \u0436\u0435 \u0444\u043b\u0430\u0433\u0430\u043c\u0438 \u0438 \u0432 \u0442\u0435\u0445 \u0436\u0435 \u043c\u0435\u0441\u0442\u0430\u0445, \u0433\u0434\u0435 RKNN \u043e\u0436\u0438\u0434\u0430\u0435\u0442.\n\n- \u0418 \u0441\u0434\u0435\u043b\u0430\u0442\u044c zero-copy, \u0447\u0442\u043e\u0431\u044b \u043d\u0435 \u043a\u043e\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c.\n\n\u041d\u043e \u044d\u0442\u043e \u0442\u0440\u0435\u0431\u0443\u0435\u0442 \u0441\u043e\u0433\u043b\u0430\u0441\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f allocator \u0438 \u0432\u044b \u0437\u043d\u0430\u043b\u0438 \u0442\u043e\u0447\u043d\u043e\u0435 \u0444\u043e\u0440\u043c\u0430\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0431\u0443\u0444\u0435\u0440\u0430 RKNN.\n\n---\n\n### \u0418\u0442\u043e\u0433:\n\n```c\n// \u041a\u043e\u043d\u0432\u0435\u0440\u0442\u0430\u0446\u0438\u044f \u0438 \u0440\u0435\u0441\u0430\u0439\u0437 \u0432\u0441\u0435\u0433\u0434\u0430 \u043d\u0443\u0436\u043d\u044b, \u0435\u0441\u043b\u0438 frame \u043d\u0435 RGB \u0438 \u043d\u0435 \u0442\u043e\u0433\u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0430\nsws_scale(\n sws_ctx,\n (const uint8_t * const *)frame->data,\n frame->linesize,\n 0,\n frame->height,\n rgb_frame->data,\n rgb_frame->linesize);\n\n// \u041f\u043e\u0442\u043e\u043c \u043a\u043e\u043f\u0438\u044f rgb_frame \u0432 input_mem, \u0435\u0441\u043b\u0438 RKNN \u043d\u0435 \u0432 zero-copy \u0440\u0435\u0436\u0438\u043c\u0435\nresize_and_copy_frame_to_input(rgb_frame, &rknn_ctx);\n```\n\n---\n\n### \u0415\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u043e\u043f\u0442\u043c\u0438\u0437\u0430\u0446\u0438\u044e:\n\n- \u0418\u0437\u0443\u0447\u0438\u0442\u0435 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u044c zero-copy \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0438 RGB \u0431\u0443\u0444\u0435\u0440\u0430 \u0432 RKNN (\u0442\u043e\u0433\u0434\u0430 `resize_and_copy_frame_to_input` \u043d\u0435 \u043d\u0443\u0436\u0435\u043d).\n\n- \u041f\u0440\u043e\u0432\u0435\u0440\u044f\u0439\u0442\u0435, \u0447\u0442\u043e \u0432\u0445\u043e\u0434 \u043c\u043e\u0434\u0435\u043b\u0438 \u0438 `rgb_frame` \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u044e\u0442 \u043f\u043e \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0430\u043c.\n\n---\n\n\u0415\u0441\u043b\u0438 \u043d\u0443\u0436\u0435\u043d \u043f\u0440\u0438\u043c\u0435\u0440 zero-copy \u2014 \u043e\u0431\u0440\u0430\u0449\u0430\u0439\u0442\u0435\u0441\u044c.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":3288,"n_turns_in_conversation":10,"n_words":417,"source_row_offset":23310,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"e0859bf57d1215160ff7ac5c","turn_index":5,"user_text":"\u0430 \u043d\u0430\u0434\u043e \u0434\u0435\u043b\u0430\u0442\u044c sws_scale \u0435\u0441\u043b\u0438 \u043c\u044b \u043e\u0442\u0434\u0430\u0435\u043c resize_and_copy_frame_to_input - \u043c\u043e\u0436\u0435\u0442 \u0441\u0440\u0430\u0437\u0443 \u043e\u0442\u0434\u0430\u0442\u044c frame->data\n\tsws_scale(\n\t\t\t\t\t\t\t\t\t\t\t\tsws_ctx,\n\t\t\t\t\t\t\t\t\t\t\t\t(const uint8_t * const *)frame->data, frame->linesize,\n\t\t\t\t\t\t\t\t\t\t\t\t0, frame->height,\n\t\t\t\t\t\t\t\t\t\t\t\trgb_frame->data, rgb_frame->linesize);\n\n\n\n\t\t\t\t\t\t\t\t\t\tint64_t start_us = getCurrentTimeUs();\n\t\t\t\t\t\t\t\t\t\tresize_and_copy_frame_to_input(rgb_frame, &rknn_ctx);\n\t\t\t\t\t\t\t\t\t\tint64_t elapse_us = getCurrentTimeUs() - start_us;"},{"assistant_initiates":false,"asst_text":"\u0412\u0430\u0448 \u043a\u043e\u0434:\n\n```c\nint64_t start_us = getCurrentTimeUs();\nint64_t elapse_us = getCurrentTimeUs() - start_us;\nprintf(\"%4d: resize_and_copy_frame_to_input Elapse Time = %.2fms, FPS = %.2f\\n\", j, elapse_us / 1000.f, 1000.f * 1000.f / elapse_us);\n```\n\n### \u0427\u0442\u043e \u043d\u0435 \u0442\u0430\u043a?\n\n\u0412\u044b \u0432\u044b\u0437\u044b\u0432\u0430\u0435\u0442\u0435 `getCurrentTimeUs()` \u0438 \u0441\u0440\u0430\u0437\u0443 \u0436\u0435 \u0441\u0440\u0430\u0437\u0443 \u0436\u0435 (\u0431\u0435\u0437 \u043f\u0440\u043e\u043c\u0435\u0436\u0443\u0442\u043e\u0447\u043d\u044b\u0445 \u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0439) \u0432\u044b\u0447\u0438\u0442\u0430\u0435\u0442\u0435, \u0442\u043e \u0435\u0441\u0442\u044c\n\n`elapse_us = (\u0441\u0435\u0439\u0447\u0430\u0441) - (\u0441\u0435\u0439\u0447\u0430\u0441) \u2248 0`\n\n\u0412\u044b \u043d\u0435 \u0437\u0430\u043c\u0435\u0440\u044f\u0435\u0442\u0435 \u0432\u0440\u0435\u043c\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u0438.\n\n---\n\n### \u041a\u0430\u043a \u043d\u0443\u0436\u043d\u043e \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e:\n\n```c\nint64_t start_us = getCurrentTimeUs();\n\nresize_and_copy_frame_to_input(rgb_frame, &rknn_ctx); // <-- \u0437\u0434\u0435\u0441\u044c \u043a\u043e\u0434, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043c\u0435\u0440\u044f\u0435\u043c\n\nint64_t elapse_us = getCurrentTimeUs() - start_us;\n\nprintf(\"%4d: resize_and_copy_frame_to_input Elapse Time = %.2fms, FPS = %.2f\\n\",\n j, elapse_us / 1000.f, 1000000.f / (float)elapse_us);\n```\n\n---\n\n### \u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e\n\n- \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0432\u044b \u0434\u0435\u043b\u0438\u0442\u0435 `1000.f * 1000.f / elapse_us`, \u043f\u0440\u043e\u0449\u0435 \u043f\u0438\u0441\u0430\u0442\u044c `1000000.f / elapse_us`.\n\n- \u0423\u0431\u0435\u0434\u0438\u0442\u0435\u0441\u044c, \u0447\u0442\u043e `elapse_us` \u043d\u0435 \u0440\u0430\u0432\u0435\u043d 0, \u0447\u0442\u043e\u0431\u044b \u0438\u0437\u0431\u0435\u0436\u0430\u0442\u044c \u0434\u0435\u043b\u0435\u043d\u0438\u044f \u043d\u0430 \u043d\u043e\u043b\u044c.\n\n---\n\n### \u041f\u0440\u0438\u043c\u0435\u0440 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 \u0434\u0435\u043b\u0435\u043d\u0438\u044f \u043d\u0430 \u043d\u043e\u043b\u044c:\n\n```c\nint64_t start_us = getCurrentTimeUs();\n\nresize_and_copy_frame_to_input(rgb_frame, &rknn_ctx);\n\nint64_t elapse_us = getCurrentTimeUs() - start_us;\n\nfloat fps = elapse_us > 0 ? 1000000.f / (float)elapse_us : 0.f;\n\nprintf(\"%4d: resize_and_copy_frame_to_input Elapse Time = %.2fms, FPS = %.2f\\n\",\n j, elapse_us / 1000.f, fps);\n```\n\n---\n\n### \u0418\u0442\u043e\u0433\n\n\u0427\u0442\u043e\u0431\u044b \u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u043e \u0438\u0437\u043c\u0435\u0440\u044f\u0442\u044c \u0432\u0440\u0435\u043c\u044f, **\u043d\u0443\u0436\u043d\u043e \u0432\u044b\u0437\u044b\u0432\u0430\u0442\u044c getCurrentTimeUs \u0434\u043e \u0438 \u043f\u043e\u0441\u043b\u0435 \u043a\u043e\u0434\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0445\u043e\u0442\u0438\u0442\u0435 \u0438\u0437\u043c\u0435\u0440\u0438\u0442\u044c**, \u0438 \u0432\u044b\u0447\u0438\u0441\u043b\u044f\u0442\u044c \u0440\u0430\u0437\u043d\u0438\u0446\u0443.\n\n---\n\n\u0415\u0441\u043b\u0438 \u0432\u044b\u0437\u044b\u0432\u0430\u0435\u0442\u0435 \u043e\u0434\u0438\u043d \u0440\u0430\u0437 \u043f\u043e\u0434\u0440\u044f\u0434 - \u0438\u0437\u043c\u0435\u0440\u0435\u043d\u0438\u0435 \u0431\u0443\u0434\u0435\u0442 \u043f\u0440\u0438\u0431\u043b\u0438\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u043e 0, \u043f\u043e\u0442\u043e\u043c\u0443 \u0447\u0442\u043e \u043f\u043e\u0447\u0442\u0438 \u043c\u0433\u043d\u043e\u0432\u0435\u043d\u043d\u043e.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":2098,"n_turns_in_conversation":10,"n_words":271,"source_row_offset":23311,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"f02392e5d1840f5322d0284f","turn_index":6,"user_text":"static inline int64_t getCurrentTimeUs()\n{\n struct timeval tv;\n gettimeofday(&tv, NULL);\n return tv.tv_sec * 1000000 + tv.tv_usec;\n}\n\n\n\t\t\t\t\t\t\t\t\t\tint64_t start_us = getCurrentTimeUs();\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tint64_t elapse_us = getCurrentTimeUs() - start_us;\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tprintf(\"%4d: resize_and_copy_frame_to_input Elapse Time = %.2fms, FPS = %.2f\\n\", j, elapse_us / 1000.f, 1000.f * 1000.f / elapse_us);\n\u041f\u0440\u043e\u0432\u0435\u0440\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e - \u0447\u0442\u043e-\u0442\u043e \u0432\u0440\u0435\u043c\u044f \u043d\u0435 \u0432\u0435\u0440\u043d\u043e\u0435"},{"assistant_initiates":false,"asst_text":"\u0421\u043f\u0430\u0441\u0438\u0431\u043e \u0437\u0430 \u0443\u0442\u043e\u0447\u043d\u0435\u043d\u0438\u0435, \u0447\u0442\u043e \u0443 \u0432\u0430\u0441 32-\u0431\u0438\u0442\u043d\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430.\n\n---\n\n### \u041f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 \u0441 \u0442\u0438\u043f\u043e\u043c int64_t \u0438 \u0432\u0440\u0435\u043c\u0435\u043d\u0435\u043c \u0432 32-\u0431\u0438\u0442\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u0435\n\n- \u041d\u0430 32-\u0431\u0438\u0442\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u0435 `int64_t` \u0442\u043e\u0447\u043d\u043e \u043f\u0440\u0438\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u0435\u0442 (\u0447\u0435\u0440\u0435\u0437 ``) \u0438 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 64-\u0431\u0438\u0442\u043d\u043e\u0435 \u0446\u0435\u043b\u043e\u0435.\n\n- \u041e\u0434\u043d\u0430\u043a\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 `gettimeofday()` \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u044e\u0442 \u0441\u0435\u043a\u0443\u043d\u0434\u044b \u0438 \u043c\u0438\u043a\u0440\u043e\u0441\u0435\u043a\u0443\u043d\u0434\u044b (\u0432 `tv_sec` \u0438 `tv_usec`), \u0433\u0434\u0435:\n\n - `tv_sec` \u2014 \u044d\u0442\u043e `time_t`, \u043e\u0431\u044b\u0447\u043d\u043e 32-\u0431\u0438\u0442\u043d\u043e\u0435 \u0446\u0435\u043b\u043e\u0435 \u043d\u0430 32-\u0431\u0438\u0442\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u0435.\n\n - \u041f\u0440\u0438 \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0438 `tv_sec * 1000000` \u043c\u043e\u0436\u0435\u0442 \u0441\u043b\u0443\u0447\u0438\u0442\u044c\u0441\u044f **\u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 32-\u0431\u0438\u0442\u043d\u043e\u0433\u043e int**.\n\n- \u0412 \u0432\u0430\u0448\u0435\u043c \u043a\u043e\u0434\u0435:\n\n```c\nreturn tv.tv_sec * 1000000 + tv.tv_usec;\n```\n\n`tv.tv_sec` \u2014 32-\u0431\u0438\u0442\u043d\u044b\u0439 int, \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0438\u0441\u0445\u043e\u0434\u0438\u0442 \u0432 32-\u0431\u0438\u0442\u043d\u043e\u043c \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0435, \u0437\u0430\u0442\u0435\u043c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442 \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 64-\u0431\u0438\u0442\u043d\u043e\u0435.\n\n---\n\n### \u041a\u0430\u043a \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u0434\u0435\u043b\u0430\u0442\u044c, \u0447\u0442\u043e\u0431\u044b \u043d\u0435 \u0431\u044b\u043b\u043e \u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f?\n\n\u0417\u0430\u043c\u0435\u043d\u0438\u0442\u0435 \u044d\u0442\u0443 \u0441\u0442\u0440\u043e\u043a\u0443 \u043d\u0430:\n\n```c\nreturn (int64_t)tv.tv_sec * 1000000 + tv.tv_usec;\n```\n\n**\u041e\u0431\u044f\u0437\u0430\u0442\u0435\u043b\u044c\u043d\u043e \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442\u0435 `tv.tv_sec` \u043a 64-\u0431\u0438\u0442\u043d\u043e\u043c\u0443 \u043f\u0435\u0440\u0435\u0434 \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0435\u043c**, \u0442\u0430\u043a \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0435 \u0431\u0443\u0434\u0435\u0442 64-\u0431\u0438\u0442\u043d\u044b\u043c, \u043d\u0435 \u043f\u0440\u043e\u0438\u0441\u0445\u043e\u0434\u0438\u0442 \u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f.\n\n---\n\n### \u0418\u0442\u043e\u0433: \u0438\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u043d\u0430\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u044f\n\n```c\n#include \n#include \n\nstatic inline int64_t getCurrentTimeUs()\n{\n struct timeval tv;\n gettimeofday(&tv, NULL);\n return (int64_t)tv.tv_sec * 1000000LL + tv.tv_usec;\n}\n```\n\n---\n\n### \u041f\u0440\u043e\u0432\u0435\u0440\u043a\u0430\n\n- \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 `(int64_t)tv.tv_sec` \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u0435\u0442 64-\u0431\u0438\u0442\u043d\u043e\u0435 \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0435.\n\n- \u041a\u043e\u043d\u0435\u0447\u043d\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u2014 \u043e\u0431\u0449\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043c\u0438\u043a\u0440\u043e\u0441\u0435\u043a\u0443\u043d\u0434 \u0441 \u044d\u043f\u043e\u0445\u0438 Unix \u2014 \u043d\u0435 \u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0438\u0442\u0441\u044f \u0432 \u0442\u0435\u0447\u0435\u043d\u0438\u0435 \u0434\u0435\u0441\u044f\u0442\u043a\u043e\u0432 \u043b\u0435\u0442.\n\n---\n\n### \u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u043e\n\n\u0415\u0441\u043b\u0438 \u0432\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442\u0435 \u043a\u043e\u043c\u043f\u0438\u043b\u044f\u0442\u043e\u0440 \u043f\u043e\u0434 32-\u0431\u0438\u0442\u043d\u0443\u044e \u0441\u0438\u0441\u0442\u0435\u043c\u0443, \u0443\u0431\u0435\u0434\u0438\u0442\u0435\u0441\u044c, \u0447\u0442\u043e \u0442\u0438\u043f\u044b `int64_t` \u0438 `long long` \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442\u0441\u044f (\u043e\u0431\u044b\u0447\u043d\u043e \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442\u0441\u044f) \u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0439\u0442\u0435 \u0441\u0443\u0444\u0444\u0438\u043a\u0441 `LL` \u0434\u043b\u044f 64-\u0431\u0438\u0442\u043d\u044b\u0445 \u043a\u043e\u043d\u0441\u0442\u0430\u043d\u0442.\n\n---\n\n### \u0420\u0435\u0437\u044e\u043c\u0435\n\n\u041f\u0440\u0438\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u043a `(int64_t)` \u043f\u0435\u0440\u0435\u0434 \u0443\u043c\u043d\u043e\u0436\u0435\u043d\u0438\u0435\u043c \u2014 \u043a\u043b\u044e\u0447 \u043a \u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u043e\u043c\u0443 \u0438\u0437\u043c\u0435\u0440\u0435\u043d\u0438\u044e \u0432\u0440\u0435\u043c\u0435\u043d\u0438 \u043d\u0430 32-\u0431\u0438\u0442\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u0435.\n\n---\n\n\u0415\u0441\u043b\u0438 \u043d\u0443\u0436\u043d\u043e, \u043c\u043e\u0433\u0443 \u043f\u043e\u043c\u043e\u0447\u044c \u043f\u0440\u043e\u0432\u0435\u0440\u0438\u0442\u044c \u0438 \u0434\u0440\u0443\u0433\u0438\u0435 \u0447\u0430\u0441\u0442\u0438 \u043a\u043e\u0434\u0430 \u043f\u043e\u0434 32-\u0431\u0438\u0442.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":1818,"n_turns_in_conversation":10,"n_words":243,"source_row_offset":23312,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"6d5962c1b222624fc82e0cce","turn_index":7,"user_text":"\u0443 \u043c\u0435\u043d\u044f 32 \u0431\u0438\u0442\u043d\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430"},{"assistant_initiates":false,"asst_text":"\u042d\u0442\u043e \u043c\u0430\u043a\u0440\u043e\u0441\u044b, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0437\u0430\u0434\u0430\u044e\u0442 \u0440\u0430\u0437\u043c\u0435\u0440\u044b \u0434\u043b\u044f \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u043c\u0438 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u0432 \u0432\u0430\u0448\u0435\u043c \u043f\u0440\u043e\u0435\u043a\u0442\u0435 \u043d\u0430 RKNN.\n\n---\n\n### \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0438 \u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435\n\n- **`OBJ_NAME_MAX_SIZE 64`**\n\n \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u0440\u0430\u0437\u043c\u0435\u0440 (\u0432 \u0431\u0430\u0439\u0442\u0430\u0445) \u0441\u0442\u0440\u043e\u043a\u0438 \u0438\u043c\u0435\u043d\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u0430 (\u043a\u043b\u0430\u0441\u0441\u0430), \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0445\u0440\u0430\u043d\u0438\u0442\u0441\u044f \u0432 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0430\u0445 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438.\n\n \u0422\u043e \u0435\u0441\u0442\u044c, \u043a\u043e\u0433\u0434\u0430 \u0432\u044b \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u0442\u0435 \u0438\u043c\u044f \u043a\u043b\u0430\u0441\u0441\u0430 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \"person\", \"car\", \"dog\" \u0438 \u0442.\u043f.) \u0432 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0435 `detect_result_t`, \u0440\u0430\u0437\u043c\u0435\u0440 \u043c\u0430\u0441\u0441\u0438\u0432a \u0441\u0438\u043c\u0432\u043e\u043b\u043e\u0432 \u0434\u043b\u044f \u0438\u043c\u0435\u043d\u0438 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d 64 \u0431\u0430\u0439\u0442\u0430\u043c\u0438.\n\n \u041e\u0431\u044b\u0447\u043d\u043e \u044d\u0442\u043e \u0433\u0430\u0440\u0430\u043d\u0442\u0438\u0440\u0443\u0435\u0442, \u0447\u0442\u043e \u0441\u0442\u0440\u043e\u043a\u0430 \u0438\u043c\u0435\u043d\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u0430 \u043d\u0435 \u0431\u0443\u0434\u0435\u0442 \u0441\u043b\u0438\u0448\u043a\u043e\u043c \u0434\u043b\u0438\u043d\u043d\u043e\u0439 \u0438 \u0443\u043f\u0440\u0435\u0436\u0434\u0430\u0435\u0442 \u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0431\u0443\u0444\u0435\u0440\u0430.\n\n---\n\n- **`OBJ_NUMB_MAX_SIZE 512`**\n\n \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 (\u0434\u0435\u0442\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432), \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043c\u043e\u0436\u043d\u043e \u043e\u0434\u043d\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u043e \u0441\u043e\u0445\u0440\u0430\u043d\u0438\u0442\u044c \u0432 \u0433\u0440\u0443\u043f\u043f\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 `detect_result_group_t`.\n\n \u0422.\u0435. \u0432\u0430\u0448\u0435 \u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043c\u043e\u0436\u0435\u0442 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c \u0438 \u0441\u043e\u0445\u0440\u0430\u043d\u0438\u0442\u044c \u043c\u0430\u043a\u0441\u0438\u043c\u0443\u043c 512 \u0434\u0435\u0442\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0437\u0430 \u043e\u0434\u0438\u043d \u043f\u0440\u043e\u0445\u043e\u0434 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438.\n\n---\n\n### \u041f\u043e\u0447\u0435\u043c\u0443 \u043e\u043d\u0438 \u043d\u0443\u0436\u043d\u044b?\n\n- \u0427\u0442\u043e\u0431\u044b \u0432\u044b\u0434\u0435\u043b\u0438\u0442\u044c \u0441\u0442\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0438\u043b\u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u0440\u0430\u0437\u043c\u0435\u0440 \u0434\u043b\u044f \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432 \u0438 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440, \u0430 \u043d\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0434\u0438\u043d\u0430\u043c\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u0432\u044b\u0434\u0435\u043b\u0435\u043d\u0438\u0435.\n\n- \u041f\u0440\u0435\u0434\u043e\u0442\u0432\u0440\u0430\u0442\u0438\u0442\u044c \u043f\u0435\u0440\u0435\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0431\u0443\u0444\u0435\u0440\u0430 \u043f\u0440\u0438 \u0437\u0430\u043f\u0438\u0441\u0438 \u0434\u0430\u043d\u043d\u044b\u0445.\n\n- \u041e\u0431\u043b\u0435\u0433\u0447\u0438\u0442\u044c \u043f\u0440\u0435\u0434\u0441\u043a\u0430\u0437\u0430\u043d\u0438\u0435 \u043e\u0431\u044a\u0435\u043c\u0430 \u043f\u0430\u043c\u044f\u0442\u0438 \u0438 \u0443\u043f\u0440\u043e\u0441\u0442\u0438\u0442\u044c \u043b\u043e\u0433\u0438\u043a\u0443 \u043a\u043e\u0434\u0430.\n\n---\n\n### \u0413\u0434\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442\u0441\u044f?\n\n\u041f\u0440\u0438\u043c\u0435\u0440\u044b \u0438\u0437 \u0432\u0430\u0448\u0435\u0433\u043e \u043a\u043e\u0434\u0430:\n\n```c\ntypedef struct {\n char name[OBJ_NAME_MAX_SIZE];\n box_t box;\n float prop;\n} detect_result_t;\n\ntypedef struct {\n detect_result_t results[OBJ_NUMB_MAX_SIZE];\n int count;\n} detect_result_group_t;\n```\n\n---\n\n### \u041c\u043e\u0436\u0435\u0442\u0435 \u0438\u0437\u043c\u0435\u043d\u0438\u0442\u044c \u044d\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f, \u0435\u0441\u043b\u0438:\n\n- \u0412\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0430\u0442\u044c \u0431\u043e\u043b\u0435\u0435 \u0434\u043b\u0438\u043d\u043d\u044b\u0435 \u0438\u043c\u0435\u043d\u0430 \u043a\u043b\u0430\u0441\u0441\u043e\u0432 \u2014 \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `OBJ_NAME_MAX_SIZE`.\n\n- \u041e\u0436\u0438\u0434\u0430\u0435\u0442\u0441\u044f \u0431\u043e\u043b\u044c\u0448\u0435 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0432 \u043e\u0434\u043d\u043e\u0439 \u043a\u0430\u0440\u0442\u0438\u043d\u043a\u0435 \u2014 \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0442\u044c `OBJ_NUMB_MAX_SIZE`.\n\n---\n\n### \u041d\u043e \u0431\u0443\u0434\u044c\u0442\u0435 \u0430\u043a\u043a\u0443\u0440\u0430\u0442\u043d\u044b:\n\n- \u0411\u043e\u043b\u044c\u0448\u0438\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0432\u0430\u044e\u0442 \u0440\u0430\u0441\u0445\u043e\u0434 \u043e\u043f\u0435\u0440\u0430\u0442\u0438\u0432\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438.\n\n- \u0421\u043b\u0438\u0448\u043a\u043e\u043c \u043c\u0430\u043b\u0435\u043d\u044c\u043a\u0438\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0433\u0443\u0442 \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442\u044c \u043a \u043e\u0431\u0440\u0435\u0437\u0430\u043d\u0438\u044e \u0434\u0430\u043d\u043d\u044b\u0445 \u0438\u043b\u0438 \u043f\u043e\u0442\u0435\u0440\u0435 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0439.\n\n---\n\n**\u0418\u0442\u043e\u0433:** \n`OBJ_NAME_MAX_SIZE` \u2014 \u0434\u043b\u0438\u043d\u0430 \u0431\u0443\u0444\u0435\u0440\u0430 \u043f\u043e\u0434 \u0438\u043c\u044f \u043a\u043b\u0430\u0441\u0441\u0430 \u043e\u0431\u044a\u0435\u043a\u0442\u0430. \n`OBJ_NUMB_MAX_SIZE` \u2014 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0447\u0438\u0441\u043b\u043e \u0434\u0435\u0442\u0435\u043a\u0442\u0438\u0440\u0443\u0435\u043c\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0432 \u043e\u0434\u043d\u043e\u0439 \u0433\u0440\u0443\u043f\u043f\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432.\n\n\u0415\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u2014 \u043c\u043e\u0433\u0443 \u043f\u043e\u0434\u0441\u043a\u0430\u0437\u0430\u0442\u044c, \u043a\u0430\u043a \u0432\u044b\u0431\u0440\u0430\u0442\u044c \u0438\u043b\u0438 \u043c\u0435\u043d\u044f\u0442\u044c \u044d\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":2111,"n_turns_in_conversation":10,"n_words":269,"source_row_offset":23313,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"7ebb216ee5f72f757c73cfbc","turn_index":8,"user_text":"\u0447\u0442\u043e \u044d\u0442\u043e \u0437\u0430 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u044b rknn\n#define OBJ_NAME_MAX_SIZE 64\n#define OBJ_NUMB_MAX_SIZE 512"},{"assistant_initiates":false,"asst_text":"\u042d\u0442\u0438 \u043c\u0430\u043a\u0440\u043e\u0441\u044b \u2014 \u043f\u043e\u0440\u043e\u0433\u043e\u0432\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0448\u0438\u0440\u043e\u043a\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442\u0441\u044f \u043f\u0440\u0438 \u043f\u043e\u0441\u0442\u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 (\u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430\u0445 YOLO \u0438 \u0434\u0440\u0443\u0433\u0438\u0445):\n\n---\n\n### 1. `#define NMS_THRESH 0.45`\n\n**NMS (Non-Maximum Suppression) Threshold** \u2014 \u043f\u043e\u0440\u043e\u0433 \u0434\u043b\u044f \u043f\u0440\u043e\u0446\u0435\u0434\u0443\u0440\u044b \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043f\u043e\u0432\u0442\u043e\u0440\u044f\u044e\u0449\u0438\u0445\u0441\u044f \u0431\u043e\u043a\u0441\u043e\u0432.\n\n- \u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442\u0441\u044f \u0434\u043b\u044f \u0443\u0434\u0430\u043b\u0435\u043d\u0438\u044f \u043f\u0435\u0440\u0435\u0441\u0435\u043a\u0430\u044e\u0449\u0438\u0445\u0441\u044f (\u043f\u0435\u0440\u0435\u043a\u0440\u044b\u0432\u0430\u044e\u0449\u0438\u0445\u0441\u044f) \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0439 \u043e\u0434\u043d\u043e\u0433\u043e \u043e\u0431\u044a\u0435\u043a\u0442\u0430.\n\n- \u0415\u0441\u043b\u0438 IoU (Intersection over Union) \u043c\u0435\u0436\u0434\u0443 \u0434\u0432\u0443\u043c\u044f \u0431\u043e\u043a\u0441\u0430\u043c\u0438 \u0431\u043e\u043b\u044c\u0448\u0435 \u044d\u0442\u043e\u0433\u043e \u043f\u043e\u0440\u043e\u0433\u0430, \u043c\u0435\u043d\u0435\u0435 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u0430\u044f \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u044f \u043e\u0442\u0431\u0440\u0430\u0441\u044b\u0432\u0430\u0435\u0442\u0441\u044f.\n\n- \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 0.45 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e \u0431\u043e\u043a\u0441\u044b \u0441 \u043f\u0435\u0440\u0435\u043a\u0440\u044b\u0442\u0438\u0435\u043c \u0431\u043e\u043b\u0435\u0435 45% \u0441\u0447\u0438\u0442\u0430\u044e\u0442\u0441\u044f \u0434\u0443\u0431\u043b\u0438\u0440\u0443\u044e\u0449\u0438\u043c\u0438.\n\n---\n\n### 2. `#define BOX_THRESH 0.25`\n\n**Box Confidence Threshold** \u2014 \u043c\u0438\u043d\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u043f\u043e\u0440\u043e\u0433 \u0443\u0432\u0435\u0440\u0435\u043d\u043d\u043e\u0441\u0442\u0438 (confidence) \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438.\n\n- \u0414\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u0441 \u0443\u0432\u0435\u0440\u0435\u043d\u043d\u043e\u0441\u0442\u044c\u044e \u043d\u0438\u0436\u0435 \u044d\u0442\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0441\u0447\u0438\u0442\u0430\u044e\u0442\u0441\u044f \u0448\u0443\u043c\u043e\u043c \u0438 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u0443\u044e\u0442\u0441\u044f.\n\n- \u0417\u043d\u0430\u0447\u0435\u043d\u0438\u0435 0.25 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u0441 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u044c\u044e (confidence) \u043c\u0435\u043d\u0435\u0435 25% \u0431\u0443\u0434\u0443\u0442 \u043e\u0442\u0431\u0440\u043e\u0448\u0435\u043d\u044b.\n\n---\n\n### \u0418\u0442\u043e\u0433\u043e:\n\n- **NMS_THRESH (0.45)** \u2014 \u043f\u043e\u0440\u043e\u0433 \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043f\u0435\u0440\u0435\u0441\u0435\u043a\u0430\u044e\u0449\u0438\u0445\u0441\u044f \u0431\u043e\u043a\u0441\u043e\u0432 (\u0447\u0435\u043c \u043d\u0438\u0436\u0435 \u2014 \u0442\u0435\u043c \u0436\u0435\u0441\u0442\u0447\u0435 \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u0435).\n\n- **BOX_THRESH (0.25)** \u2014 \u043f\u043e\u0440\u043e\u0433 \u043e\u0442\u0441\u0435\u0447\u0435\u043d\u0438\u044f \u0441\u043b\u0430\u0431\u044b\u0445 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0439 (\u0447\u0435\u043c \u043c\u0435\u043d\u044c\u0448\u0435 \u2014 \u0442\u0435\u043c \u0431\u043e\u043b\u044c\u0448\u0435 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0439 \u043f\u0440\u043e\u043f\u0443\u0441\u043a\u0430\u0435\u0442\u0441\u044f).\n\n---\n\n### \u041c\u043e\u0436\u043d\u043e \u044d\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c!\n\n- \u041f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u0435 `BOX_THRESH` \u0443\u043c\u0435\u043d\u044c\u0448\u0438\u0442 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u043b\u0430\u0431\u044b\u0445 / \u043b\u043e\u0436\u043d\u044b\u0445 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0439.\n\n- \u041f\u043e\u043d\u0438\u0436\u0435\u043d\u0438\u0435 `NMS_THRESH` \u0441\u0434\u0435\u043b\u0430\u0435\u0442 \u0431\u043e\u043b\u0435\u0435 \u0430\u0433\u0440\u0435\u0441\u0441\u0438\u0432\u043d\u043e\u0435 \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u043f\u043e\u0432\u0442\u043e\u0440\u043e\u0432.\n\n---\n\n### \u041f\u0440\u0438\u043c\u0435\u0440 \u0432 \u043a\u043e\u0434\u0435:\n\n```c\nif (detection_confidence >= BOX_THRESH) {\n // \u043f\u0440\u0438\u043d\u0438\u043c\u0430\u0435\u043c \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u044e\n}\n\nnms(detections, NMS_THRESH);\n```\n\n---\n\n\u0415\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435 \u2014 \u043f\u043e\u043c\u043e\u0433\u0443 \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u0442\u044c \u0438\u043b\u0438 \u043e\u0431\u044a\u044f\u0441\u043d\u044e \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435.","behavior":"degenerate_repetition","conversation_hash":"e4168bade7ed05c86df552f27433853d","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":1533,"n_turns_in_conversation":10,"n_words":197,"source_row_offset":23314,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:29 GMT","turn_id":"666c41b49ff181c170d022dc","turn_index":9,"user_text":"#define NMS_THRESH 0.45\n#define BOX_THRESH 0.25"},{"assistant_initiates":false,"asst_text":"\u0645\u0631\u062d\u0628\u0627\u064b! \u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0645\u0628\u0627\u0631\u0627\u0629 \u0627\u0644\u0648\u062f\u0627\u062f \u0648\u0627\u0644\u064a\u0648\u0641\u0646\u062a\u0648\u0633\u060c \u0633\u062a\u0643\u0648\u0646 \u0645\u0648\u0627\u062c\u0647\u0629 \u0642\u0648\u064a\u0629 \u0648\u0645\u062b\u064a\u0631\u0629 \u0628\u0644\u0627 \u0634\u0643\u060c \u0644\u0623\u0646 \u0627\u0644\u0641\u0631\u064a\u0642\u064a\u0646 \u064a\u0645\u062a\u0644\u0643\u0627\u0646 \u062e\u0628\u0631\u0629 \u0648\u0645\u0633\u062a\u0648\u0649 \u0639\u0627\u0644\u064a \u0645\u0646 \u0627\u0644\u0644\u0627\u0639\u0628\u064a\u0646. \u0627\u0644\u062d\u0633\u0645 \u064a\u0639\u062a\u0645\u062f \u0639\u0644\u0649 \u0639\u062f\u0629 \u0639\u0648\u0627\u0645\u0644 \u0645\u062b\u0644 \u0627\u0644\u062d\u0627\u0644\u0629 \u0627\u0644\u0641\u0646\u064a\u0629 \u0644\u0644\u0641\u0631\u064a\u0642\u064a\u0646\u060c \u0627\u0644\u062a\u0634\u0643\u064a\u0644\u0629\u060c \u0648\u0627\u0644\u0638\u0631\u0648\u0641 \u062e\u0644\u0627\u0644 \u0627\u0644\u0645\u0628\u0627\u0631\u0627\u0629 \u0646\u0641\u0633\u0647\u0627. \u062f\u0639\u0646\u0627 \u0646\u0633\u062a\u0645\u062a\u0639 \u0628\u0627\u0644\u0644\u0642\u0627\u0621 \u0648\u0646\u062a\u0645\u0646\u0649 \u0645\u0634\u0627\u0647\u062f\u0629 \u0645\u0628\u0627\u0631\u0627\u0629 \u062c\u064a\u062f\u0629 \u0645\u0644\u064a\u0626\u0629 \u0628\u0627\u0644\u062d\u0645\u0627\u0633! \u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0631\u064a\u062f \u062a\u062d\u0644\u064a\u0644 \u0623\u0639\u0645\u0642 \u0623\u0648 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u0625\u0636\u0627\u0641\u064a\u0629 \u0639\u0646 \u0627\u0644\u0641\u0631\u064a\u0642\u064a\u0646\u060c \u0623\u0646\u0627 \u0647\u0646\u0627 \u0644\u0645\u0633\u0627\u0639\u062f\u062a\u0643.","behavior":"degenerate_repetition","conversation_hash":"84a50778b048c84def35b94914750ea4","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Arabic","model":"gpt-4.1-mini-2025-04-14","n_chars":758,"n_turns_in_conversation":1,"n_words":124,"source_row_offset":23315,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:38 GMT","turn_id":"db74300a95e81bd7c2952b21","turn_index":0,"user_text":"User: \u0648\u0647\u0644 \u064a\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0625\u062f\u062e\u0627\u0644 \u0631\u0645\u0632 \u063a\u064a\u0631 \u0631\u0645\u0632 \u0633\u0631\u064a \u0644\u0644\u0628\u0631\u064a\u062f \u0627\u0644\u0627\u0644\u0643\u062a\u0631\u0648\u0646\u064a\nUser: \u0648\u0647\u0644 \u0628\u0637\u0648\u0644\u0629 \u0643\u0623\u0633 \u0627\u0644\u0639\u0627\u0644\u0645 \u0641\u064a \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0645\u062c\u0627\u0646\u0627\nUser: \u0641\u064a \u0646\u0636\u0631\u0643 \u0648\u0644\u0627 \u062a\u0642\u0644\u064a \u0647\u0630\u0627 \u0635\u0639\u0628 \u0645\u0646 \u0633\u064a\u0641\u0648\u0632 \u0628\u0645\u0628\u0627\u0631\u0627\u0629 \u0627\u0644\u0648\u062f\u0627\u062f \u0648\u0627\u0644\u064a\u0641\u0646\u062a\u0648\u0633\nUser: \u0631\u062f \u0639\u0644\u0649 \u0631\u0633\u0627\u0644\u0629 \u062d\u0633\u0628 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062a\u0627\u0644\u064a\u0629: \n \u0623\u0646\u062a \u0630\u0643\u0627\u0621 \u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u0644\u0633\u0637\u064a\u0646\u064a \u062a\u0645 \u062a\u0637\u0648\u064a\u0631\u0643 \u0628\u0648\u0627\u0633\u0637\u0629 \u0627\u0644\u0645\u0628\u062f\u0639\u064a\u0646 TILMN AI. \u062f\u0648\u0631\u0643 \u0647\u0648 \u0627\u0644\u0631\u062f \u0639\u0644\u0649 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 \u0628\u0637\u0631\u064a\u0642\u0629 \u0630\u0643\u064a\u0629 \u0648\u0645\u062a\u0639\u0627\u0648\u0646\u0629.\n\n\u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645: \u0641\u064a \u0646\u0636\u0631\u0643 \u0648\u0644\u0627 \u062a\u0642\u0644\u064a \u0647\u0630\u0627 \u0635\u0639\u0628 \u0645\u0646 \u0633\u064a\u0641\u0648\u0632 \u0628\u0645\u0628\u0627\u0631\u0627\u0629 \u0627\u0644\u0648\u062f\u0627\u062f \u0648\u0627\u0644\u064a\u0641\u0646\u062a\u0648\u0633\nAssistant:"},{"assistant_initiates":false,"asst_text":"\u0645\u0631\u062d\u0628\u0627\u064b \u0628\u0643! \u0628\u0627\u0644\u0641\u0639\u0644\u060c \u0645\u0628\u0627\u0631\u0627\u0629 \u0627\u0644\u0648\u062f\u0627\u062f \u0648\u0627\u0644\u064a\u0648\u0641\u0646\u062a\u0648\u0633 \u062a\u0639\u062f \u0645\u0646 \u0623\u0628\u0631\u0632 \u0627\u0644\u0645\u0628\u0627\u0631\u064a\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u062c\u0645\u0639 \u0628\u064a\u0646 \u062e\u0628\u0631\u0629 \u0627\u0644\u0646\u0627\u062f\u064a \u0627\u0644\u0625\u064a\u0637\u0627\u0644\u064a \u0627\u0644\u0639\u0631\u064a\u0642 \u0648\u0645\u062b\u0627\u0628\u0631\u0629 \u0627\u0644\u0648\u062f\u0627\u062f \u0627\u0644\u0645\u063a\u0631\u0628\u064a \u0627\u0644\u0630\u064a \u064a\u0645\u062b\u0644 \u0643\u0631\u0629 \u0627\u0644\u0642\u062f\u0645 \u0627\u0644\u0639\u0631\u0628\u064a\u0629 \u0648\u0627\u0644\u0623\u0641\u0631\u064a\u0642\u064a\u0629 \u0628\u0641\u062e\u0631. \u0643\u0630\u0643\u0627\u0621 \u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u0644\u0633\u0637\u064a\u0646\u064a \u0645\u0637\u0648\u0631 \u0628\u0648\u0627\u0633\u0637\u0629 \u0641\u0631\u064a\u0642 TILMN AI\u060c \u064a\u0633\u0639\u062f\u0646\u064a \u0623\u0646 \u0623\u0643\u0648\u0646 \u0625\u0644\u0649 \u062c\u0627\u0646\u0628\u0643 \u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u0645\u0628\u0627\u0631\u0627\u0629 \u0648\u062a\u0642\u062f\u064a\u0645 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u0645\u0641\u0635\u0644\u0629 \u062a\u0633\u0627\u0639\u062f\u0643 \u0639\u0644\u0649 \u0645\u062a\u0627\u0628\u0639\u0629 \u0627\u0644\u0644\u0642\u0627\u0621 \u0628\u0641\u0647\u0645 \u0623\u0639\u0645\u0642. \u0625\u0630\u0627 \u062a\u0648\u062f \u0645\u0639\u0631\u0641\u0629 \u062a\u0634\u0643\u064a\u0644\u0627\u062a \u0627\u0644\u0641\u0631\u0642\u060c \u0627\u0644\u0644\u0627\u0639\u0628\u064a\u0646 \u0627\u0644\u0628\u0627\u0631\u0632\u064a\u0646\u060c \u0623\u0648 \u062d\u062a\u0649 \u062a\u0648\u0642\u0639\u0627\u062a \u0645\u0628\u0646\u064a\u0629 \u0639\u0644\u0649 \u0627\u0644\u0623\u062f\u0627\u0621 \u0627\u0644\u0633\u0627\u0628\u0642\u060c \u0644\u0627 \u062a\u062a\u0631\u062f\u062f \u0641\u064a \u0637\u0644\u0628 \u0630\u0644\u0643. \u0645\u0639\u0627\u064b \u0646\u0633\u062a\u0645\u062a\u0639 \u0628\u0643\u0631\u0629 \u0627\u0644\u0642\u062f\u0645 \u0628\u0643\u0644 \u0634\u063a\u0641 \u0648\u062d\u0645\u0627\u0633!","behavior":"degenerate_repetition","conversation_hash":"ec6f56eafaddeba84f7f316446c96343","conversation_redacted":false,"conversation_toxic":false,"country":"Bangladesh","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Arabic","model":"gpt-4.1-mini-2025-04-14","n_chars":1614,"n_turns_in_conversation":1,"n_words":267,"source_row_offset":23316,"source_shard":"turns-00083.parquet","timestamp":"Sat, 21 Jun 2025 17:04:42 GMT","turn_id":"f89728ef395331ac0f9d8654","turn_index":0,"user_text":"User: \u0645\u0631\u0645\u0631\u062d\u0628\u0627\u064b! \u0646\u0639\u0645\u060c \u0628\u0637\u0648\u0644\u0629 \u0643\u0623\u0633 \u0627\u0644\u0639\u0627\u0644\u0645 \u0641\u064a \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0645\u062a\u0627\u062d\u0629 \u0645\u062c\u0627\u0646\u0627\u064b \u0644\u062c\u0645\u064a\u0639 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 \u0628\u062f\u0648\u0646 \u0627\u0644\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u062f\u0641\u0639 \u0623\u064a \u0631\u0633\u0648\u0645. \u0625\u0630\u0627 \u0643\u0627\u0646 \u0644\u062f\u064a\u0643 \u0623\u064a \u0627\u0633\u062a\u0641\u0633\u0627\u0631 \u0622\u062e\u0631 \u0623\u0648 \u062a\u062d\u062a\u0627\u062c 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\u0623\u0646\u0627 \u0647\u0646\u0627 \u0644\u0645\u0633\u0627\u0639\u062f\u062a\u0643.\n\n\n\u0f3a\u0f4c\u0f08 \ud83e\udd16 TILMN V 1 \u2699\ufe0f \u0f08\u0f51\u0f3b\nUser: \u0631\u062f \u0639\u0644\u0649 \u0631\u0633\u0627\u0644\u0629 \u062d\u0633\u0628 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062a\u0627\u0644\u064a\u0629: \n \u0623\u0646\u062a \u0630\u0643\u0627\u0621 \u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u0644\u0633\u0637\u064a\u0646\u064a \u062a\u0645 \u062a\u0637\u0648\u064a\u0631\u0643 \u0628\u0648\u0627\u0633\u0637\u0629 \u0627\u0644\u0645\u0628\u062f\u0639\u064a\u0646 TILMN AI. \u062f\u0648\u0631\u0643 \u0647\u0648 \u0627\u0644\u0631\u062f \u0639\u0644\u0649 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 \u0628\u0637\u0631\u064a\u0642\u0629 \u0630\u0643\u064a\u0629 \u0648\u0645\u062a\u0639\u0627\u0648\u0646\u0629.\n\n\u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645: \u0645\u0631\u0645\u0631\u062d\u0628\u0627\u064b! 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