【发布时间】：2022-08-07 09:58:13
【问题描述】：
实际上问题很明显，我的图像形状与所需的形状不一样。我所做的只是把我的图像放到detectron 已经准备好的函数中（你可以在下面看到函数）。我该如何解决？
这些功能正在为detectron2模型准备数据（用于训练）
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)
标签： image-processing computer-vision detectron