voc to yolo

import os
import cv2
import json
import shutil
import numpy as np
import pybboxes as pbx
from pybboxes import BoundingBox


def bnd_box_to_yolo_line(box, img_size):
    (x_min, y_min) = (box[0], box[1])
    (w, h) = (box[2], box[3])
    x_max = x_min + w
    y_max = y_min + h

    x_center = float((x_min + x_max)) / 2 / img_size[1]
    y_center = float((y_min + y_max)) / 2 / img_size[0]

    w = float((x_max - x_min)) / img_size[1]
    h = float((y_max - y_min)) / img_size[0]

    return (x_center, y_center, w, h)

def convert(size,box):
    dw = 1./size[0]
    dh = 1./size[1]
    x = (box[0]+box[1])/2.0
    y = (box[2]+box[3])/2.0
    w = box[1] - box[0]
    h = box[3] - box[2]
    x = x*dw
    w = w*dw
    y = y*dh
    h = h*dh
    return (x,y,w,h)

dir_path = ".\\images"

file_format = ['jpg','JPG']
for (root, directories, files) in os.walk(dir_path):
    for file in files:
        # try:
        #     img = cv2.imread(root+"\\"+file)
        #     if img.shape[0] !=640:
        #         img = cv2.resize(img,(640,640),interpolation = cv2.INTER_CUBIC)
        #         cv2.imwrite(root+"\\"+file,img)
        # except:
        #     pass
        if file_format[0] in file or file_format[1] in file:
            file_path = root+"\\"+file

            if file.find(file_format[0])>0 or file.find(file_format[1]):
                with open("labels"+"\\"+file.replace('jpg','json').replace('JPG','json'), "r",encoding="UTF-8") as st_json:
                    st_python = json.load(st_json)
                    origin_w = int(st_python['images'][0]['width'])
                    origin_h = int(st_python['images'][0]['height'])
                    annotations = st_python['annotations']
                    f = open(".\\images"+"\\"+file.replace('jpg','txt').replace('JPG','txt'), 'w')
                    img = cv2.imread(file_path)
                    for ann in annotations:
                        (xmin,ymin,xmax,ymax) = ann['bbox']
                        print(xmin,ymin,xmax,ymax)
                        x_scale = (640/origin_w)
                        y_scale = (640/origin_h)
                        print(x_scale)
                        (xmin, ymin, xmax, ymax) =  (xmin*x_scale,ymin*y_scale,xmax*x_scale,ymax*y_scale)

                        img = cv2.resize(img,(origin_w,origin_h),interpolation = cv2.INTER_CUBIC)
                        cv2.imwrite(root+"\\"+file,img)

                        my_coco_box = (xmin,ymin,xmax,ymax)
                        bb = bnd_box_to_yolo_line(my_coco_box,(640,640))
                        # coco_bbox = BoundingBox.from_voc(*my_coco_box, image_size=(640,640),strict=False)  # <[98 345 322 117] (322x117) | Image: (640x480)>

                        # no longer raises exception
                        # bb = coco_bbox.to_yolo()
                        #                        bb = convert((origin_w,origin_h),(xmin,ymin,xmax,ymax))
                        # bb   = bb.values

                        f.write(str(0) + ' ' + str(bb[0]) + " " + str(bb[1]) + " " + str(bb[2]) + " " + str(bb[3]) + "\n")
                    # cv2.imshow('rec',img)
                    f.close()
                    print(file_path)



# # b = ()
# with open("labels"+"\\09_20201013_189291.json", "r",encoding="UTF-8") as st_json:
#     st_python = json.load(st_json)
#     images = st_python['images']
#
#     annotations = st_python['annotations']
#     f = open(".\\images\\09_20201013_189291.txt", 'w')
#     x = int(images[0]['width'])
#     y = int(images[0]['height'])
#     for ann in annotations:
#         xmin,ymin,xmax,ymax = annotations[0]['bbox']
#         x_scale = 640/x
#         y_scale = 640/y
#
#
#         x = int(np.round(xmin*x_scale))
#         y = int(np.round(ymin*y_scale))
#         xmax= int(np.round(xmax*(x_scale)))
#         ymax= int(np.round(ymax*y_scale))
#         f.write(str(0) + ' ' + str(x) + " " + str(y) + " " + str(xmax) + " " + str(ymax) + "\n")
#     f.close()