json.py

coco_data = {}
coco_data["type"] = "instances"
coco_data["images"] = []
coco_data["annotations"] = []
coco_data["categories"] = list_dict
image_id = 0
annotation_id = 0


for i in tqdm(range(len(df))):
    img_name = df[columns[0]][i]
    labels = df[columns[1]][i]
    tmp = labels.split(delimiter);
    image_in_path = input_images_folder + "/" + img_name
    if(not os.path.isfile(image_in_path)):
        continue
    img = cv2.imread(image_in_path, 1)
    h, w, c = img.shape

    images_tmp = {}
    images_tmp["file_name"] = img_name
    images_tmp["height"] = h
    images_tmp["width"] = w
    images_tmp["id"] = image_id
    coco_data["images"].append(images_tmp)
    

    for j in range(len(tmp)//5):
        x1 = int(tmp[j*5+0])
        y1 = int(tmp[j*5+1])
        x2 = int(tmp[j*5+2])
        y2 = int(tmp[j*5+3])
        label = tmp[j*5+4]
        annotations_tmp = {}
        annotations_tmp["id"] = annotation_id
        annotation_id += 1
        annotations_tmp["image_id"] = image_id
        annotations_tmp["segmentation"] = []
        annotations_tmp["ignore"] = 0
        annotations_tmp["area"] = (x2-x1)*(y2-y1)
        annotations_tmp["iscrowd"] = 0
        annotations_tmp["bbox"] = [x1, y1, x2-x1, y2-y1]
        annotations_tmp["category_id"] = anno.index(label)

        coco_data["annotations"].append(annotations_tmp)
    image_id += 1

outfile =  open(output_annotation_file, 'w')
json_str = json.dumps(coco_data, indent=4)
outfile.write(json_str)
outfile.close()