bdzl2/ai-train_platform
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已添加坐标clamp，确保归一化后的x和y严格在0.0到1.0之间。

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yooooger 2026-03-09 10:58:41 +08:00
parent d06b96ece1
commit f245d972c2
1 changed files with 8 additions and 4 deletions
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12
predict/predict_yolo11seg.py
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@ -462,13 +462,13 @@ class YOLOSegmentationInference:
h, w = mask.shape h, w = mask.shape
points = [] points = []
for point in approx: for point in approx:
x = point[0][0] / w x = max(0.0, min(1.0, point[0][0] / w))
y = point[0][1] / h y = max(0.0, min(1.0, point[0][1] / h))
points.extend([x, y]) points.extend([x, y])
# 写入标签文件 # 写入标签文件
if len(points) >= 6: # 至少3个点 if len(points) >= 6: # 至少3个点
line = f"{class_id} {' '.join(map(lambda x: f'{x:.6f}', points))} {score:.6f}\n" line = f"{class_id} {' '.join(map(lambda x: f'{x:.6f}', points))}\n"
f.write(line) f.write(line)
print(f"标签文件已保存: {label_path}") print(f"标签文件已保存: {label_path}")
@ -1027,4 +1027,8 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
else : else :
print(f"错误: 输入 {zip_url} 不是有效的文件或目录") 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"
if __name__ == '__main__':
predict_images
#predict_images_share_dir(1, "road_crack", "smb://192.168.1.100/share/ai_train_platform/train.zip", "admin", "admin.123", "predictions", 0.25, True)