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共享目录识别支持(图像类)(Images)两种标识文件

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This commit is contained in:
liyubo 2025-12-08 14:05:56 +08:00
parent bdb654da09
commit 401c4eae2f
1 changed files with 40 additions and 19 deletions
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59
predict/predict_yolo11seg.py
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@ -666,7 +666,7 @@ class YOLOSegmentationInference:
推理结果列表 推理结果列表
""" """
results = [] results = []
print(f"正在处理共享目录: {input_dir} ")
try: try:
# 检查目录是否存在 # 检查目录是否存在
config = get_conf(zip_url=input_dir, user_name=user_name, pwd=pwd) config = get_conf(zip_url=input_dir, user_name=user_name, pwd=pwd)
@ -906,7 +906,7 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
# 查找指定文件夹 图像类 # 查找指定文件夹 图像类
config = get_conf(zip_url, user_name, pwd) config = get_conf(zip_url, user_name, pwd)
scanner = get_scanner(zip_url, user_name, pwd) scanner = get_scanner(zip_url, user_name, pwd)
found_paths = scanner.find_folders_by_name( image_class_paths = scanner.find_folders_by_name(
share_path=config['share'], share_path=config['share'],
folder_name='图像类', folder_name='图像类',
start_dir=config['dir'], start_dir=config['dir'],
@ -915,21 +915,28 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
current_time = datetime.now().strftime("%Y%m%d%H%M%S") current_time = datetime.now().strftime("%Y%m%d%H%M%S")
target_path = "" # 识别图片目录 target_path = "" # 识别图片目录
flag_dir_path = "" # 标识目录 flag_dir_path = "" # 标识目录
if len(found_paths) > 0: if len(image_class_paths) > 0:
# 处理目录 # 处理目录
flag_dir_path = found_paths[0] all_images_paths = []
tmpConfig = get_conf(flag_dir_path, user_name, pwd) for image_class_path in image_class_paths :
found_paths = scanner.find_folders_by_name( flag_dir_path = image_class_path
share_path=config['share'], tmpConfig = get_conf(flag_dir_path, user_name, pwd)
folder_name='Images', images_paths = scanner.find_folders_by_name(
start_dir=tmpConfig['dir'], share_path=config['share'],
max_depth=3 folder_name='Images',
) start_dir=tmpConfig['dir'],
if len(found_paths) > 0: max_depth=3
target_path = found_paths[0] )
# inference.process_image_directory_share_dir( if len(images_paths) > 0:
# input_dir=target_path, all_images_paths.extend(images_paths)
if len(all_images_paths) > 0 :
target_path = all_images_paths[0]
# inference.process_image_directory_share_dir_circle(
# task_id=task_id,
# current_time=current_time,
# input_dir_list=all_images_paths,
# user_name=user_name, # user_name=user_name,
# pwd=pwd, # pwd=pwd,
# output_dir=output_dir, # output_dir=output_dir,
@ -942,11 +949,25 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
# ) # )
# 创建并启动线程 # 创建并启动线程
thread1 = threading.Thread(target=inference.process_image_directory_share_dir_circle, args=(task_id,current_time,found_paths,user_name,pwd,output_dir,conf_threshold,iou_threshold,save_mask,save_label,show,result_save)) thread1 = threading.Thread(target=inference.process_image_directory_share_dir_circle, args=(task_id,current_time,all_images_paths,user_name,pwd,output_dir,conf_threshold,iou_threshold,save_mask,save_label,show,result_save))
# 启动线程 # 启动线程
thread1.start() thread1.start()
else: else:
print(f"错误: 输入 {zip_url} 不是有效的文件或目录") # 直接找Images目录
tmpConfig = get_conf(zip_url, user_name, pwd)
images_paths = scanner.find_folders_by_name(
share_path=config['share'],
folder_name='Images',
start_dir=tmpConfig['dir'],
max_depth=3
)
if len(images_paths) > 0:
target_path = images_paths[0]
# 创建并启动线程
thread1 = threading.Thread(target=inference.process_image_directory_share_dir_circle, args=(task_id,current_time,images_paths,user_name,pwd,output_dir,conf_threshold,iou_threshold,save_mask,save_label,show,result_save))
# 启动线程
thread1.start()
else :
print(f"错误: 输入 {zip_url} 不是有效的文件或目录")
return standardized_path(f"{target_path}_识别/{task_id}/{current_time}/{task_id}.zip"), "success" return standardized_path(f"{target_path}_识别/{task_id}/{current_time}/{task_id}.zip"), "success"