| | |
| | | from logger_config import logger |
| | | import threading |
| | | |
| | | |
| | | multiprocessing.freeze_support() |
| | | |
| | | |
| | |
| | | logger.info(f"识别结果转换为保存图片名称:, {save_name2}") |
| | | # 判断图像的清晰度 |
| | | # 保存调整尺寸后的图片 |
| | | if laplacian > 200: |
| | | if laplacian > 150: |
| | | c_ = save_path + "2/c/" |
| | | if not os.path.exists(c_): |
| | | os.makedirs(c_) |
| | |
| | | det_res[class_name] = det_res[class_name] if det_res[class_name] > scores[i] else scores[i] |
| | | else: |
| | | det_res[class_name] = scores[i] |
| | | # 如果det_res不为空,则打印det_res |
| | | if det_res != {}: |
| | | print(det_res) |
| | | logger.info(f"安全检测识别结果, {det_res}") |
| | | # 如果cass_ids中包含0,则表示有安全检测到人体 |
| | |
| | | else: |
| | | count += 1 |
| | | class_old = class_ |
| | | if class_ == "shangliao": |
| | | print(f"{class_}:{count}: {max_probability}") |
| | | logger.info(f"{class_}:{count}: {max_probability}") |
| | | |
| | | # 判断是否上料并且上料次数大于10次 |
| | | if class_ == "shangliao" and count > 10: |
| | | status = "正在上料" |
| | |
| | | predicted_class2 = np.argmax(probabilities2, axis=1)[0] |
| | | max_probability2 = np.max(probabilities2, axis=1)[0] |
| | | class_2 = hoister_position.class_names[predicted_class2] |
| | | if class_2 == "high": |
| | | print(f"-----------{class_2}:{predicted_class2}: {max_probability2}") |
| | | logger.info(f"-----------{class_2}:{predicted_class2}: {max_probability2}") |
| | | |
| | | if predicted_class2 == 0: |
| | | feeder_res = {class_2: max_probability2} |
| | | class_feeder = "aifeeder," + f"{feeder_res}" |