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Problem is obvious actually, my images shape's are not the same with the required shapes. All I'm doing is putting my images to detectron's already prepared function(you can see functions below). How can I fix it?

These functions are preparing data to detectron2 model(for training)

def get_data_dicts(directory, classes):
    dataset_dicts = []
    for filename in [file for file in os.listdir(directory) if file.endswith('.json')]:
        json_file = os.path.join(directory, filename)
        with open(json_file) as f:
            img_anns = json.load(f)

        record = {}
        
        filename = os.path.join(directory, img_anns["imagePath"])
        
        record["file_name"] = filename
        record["height"] = 700
        record["width"] = 700
      
        annos = img_anns["shapes"]
        objs = []
        for anno in annos:
            px = [a[0] for a in anno['points']] # x coord
            py = [a[1] for a in anno['points']] # y-coord
            poly = [(x, y) for x, y in zip(px, py)] # poly for segmentation
            poly = [p for x in poly for p in x]

            obj = {
                "bbox": [np.min(px), np.min(py), np.max(px), np.max(py)],
                "bbox_mode": BoxMode.XYXY_ABS,
                "category_id": classes.index(anno['label']),
                "segmentation": [poly],
                "iscrowd": 0
            }
            objs.append(obj)
        record["annotations"] = objs
        dataset_dicts.append(record)
    return dataset_dicts

classes = ['bos_el', 'dolu_el']
data_path = '/home/berkay/Masaüstü/detectron_data/'

for d in ["test", "train"]:
    DatasetCatalog.register(
        "my_" + d, 
        lambda d=d: get_data_dicts(data_path+d, classes)
    )
    MetadataCatalog.get("my_" + d).set(thing_classes=classes)
berkaiii
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  • 3

1 Answers1

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change the 700height and 700 width to your image dimensions

Swapnil Kothari
  • 1
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