已经解决！segment-anything推理指令运行后没有overlay图片

推理指令如下：

python scripts/amg.py --checkpoint sam_vit_l_0b3195.pth  --model-type vit_l  --input D:\SAM\pics\ --output D:\SAM\pics\   --device cpu --box-nms-thresh 0.5 --crop-nms-thresh 0.5

pics是文件夹，把要分割的图片全部放到文件里面即可
 

具体的修改流程如下：
第1步：修改amg.py中的def write_masks_to_folder函数，修改后函数如下

def write_masks_to_folder(masks: List[Dict[str, Any]], path: str, image: np.ndarray) -> None:
    header = "id,area,bbox_x0,bbox_y0,bbox_w,bbox_h,point_input_x,point_input_y,predicted_iou,stability_score,crop_box_x0,crop_box_y0,crop_box_w,crop_box_h"  # noqa
    metadata = [header]
    overlay = image.copy()

    for i, mask_data in enumerate(masks):
        mask = mask_data["segmentation"]
        filename = f"{i}.png"
        cv2.imwrite(os.path.join(path, filename), mask * 255)

        # Generate a random color for each mask
        color = np.random.randint(0, 255, (3,)).tolist()
        overlay[mask] = image[mask] * 0.5 + np.array(color) * 0.5

        mask_metadata = [
            str(i),
            str(mask_data["area"]),
            *[str(x) for x in mask_data["bbox"]],
            *[str(x) for x in mask_data["point_coords"][0]],
            str(mask_data["predicted_iou"]),
            str(mask_data["stability_score"]),
            *[str(x) for x in mask_data["crop_box"]],
        ]
        row = ",".join(mask_metadata)
        metadata.append(row)

    # Save the overlay image
    overlay_filename = os.path.join(path, "overlay.png")
    cv2.imwrite(overlay_filename, cv2.cvtColor(overlay, cv2.COLOR_RGB2BGR))

    metadata_path = os.path.join(path, "metadata.csv")
    with open(metadata_path, "w") as f:
        f.write("\n".join(metadata))

    return

​第2步修改amg.py中的main函数，修改后的函数如下：
 

def main(args: argparse.Namespace) -> None:
    print("Loading model...")
    sam = sam_model_registry[args.model_type](checkpoint=args.checkpoint)
    _ = sam.to(device=args.device)
    output_mode = "coco_rle" if args.convert_to_rle else "binary_mask"
    amg_kwargs = get_amg_kwargs(args)
    generator = SamAutomaticMaskGenerator(sam, output_mode=output_mode, **amg_kwargs)

    if not os.path.isdir(args.input):
        targets = [args.input]
    else:
        targets = [
            f for f in os.listdir(args.input) if not os.path.isdir(os.path.join(args.input, f))
        ]
        targets = [os.path.join(args.input, f) for f in targets]

    os.makedirs(args.output, exist_ok=True)

    for t in targets:
        print(f"Processing '{t}'...")
        image = cv2.imread(t)
        if image is None:
            print(f"Could not load '{t}' as an image, skipping...")
            continue
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)  # Convert to RGB for processing

        masks = generator.generate(image)

        base = os.path.basename(t)
        base = os.path.splitext(base)[0]
        save_base = os.path.join(args.output, base)
        if output_mode == "binary_mask":
            os.makedirs(save_base, exist_ok=True)  # Allow existing directories
            write_masks_to_folder(masks, save_base, image)  # Pass the original image here
        else:
            save_file = save_base + ".json"
            with open(save_file, "w") as f:
                json.dump(masks, f)
    print("Done!")

最后运行完毕就生成overlay图片了