csv2labelme.py

import os
import cv2
import json
import pandas as pd
import numpy as np
import base64
image_path = "./images/"
csv_file = "./train_labels.csv"
annotations = pd.read_csv(csv_file,header=None).values
total_csv_annotations = {}
for annotation in annotations:
    key = annotation[0].split(os.sep)[-1]
    value = np.array([annotation[1:]])
    if key in total_csv_annotations.keys():
        total_csv_annotations[key] = np.concatenate((total_csv_annotations[key],value),axis=0)
    else:
        total_csv_annotations[key] = value
for key,value in total_csv_annotations.items():
    height,width = cv2.imread(image_path+key).shape[:2]
    labelme_format = {
    "version":"3.6.16",
    "flags":{},
    "lineColor":[0,255,0,128],
    "fillColor":[255,0,0,128],
    "imagePath":key,
    "imageHeight":height,
    "imageWidth":width
    }
    with open(image_path+key,"rb") as f:
        imageData = f.read()
        imageData = base64.b64encode(imageData).decode('utf-8')
    #img = utils.img_b64_to_arr(imageData)
    labelme_format["imageData"] = imageData
    shapes = []
    for shape in value:
        label = shape[-1]
        s = {"label":label,"line_color":None,"fill_color":None,"shape_type":"rectangle"}
        points = [
            [shape[0],shape[1]],
            [shape[2],shape[3]]
            ]
        s["points"] = points
        shapes.append(s)
    labelme_format["shapes"] = shapes
    save_path = os.path.join(image_path, key.replace(".jpg", ".json"))
    json.dump(labelme_format, open(save_path, "w"), ensure_ascii=False, indent=2)