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Label.py
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Label.py
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import cv2
from PIL import Image, ImageDraw
import os.path as osp
import os
import numpy as np
import matplotlib.pyplot as plt
class Label:
def draw_bboxes(self, syn_images_folder, num_of_images):
for i in range(0, num_of_images):
img_filepath = osp.join(syn_images_folder, 'image_%05d.png' % i)
im = Image.open(img_filepath)
draw = ImageDraw.Draw(im)
# Open a bounding box file, read all entry and sort in x-direction distance
bbox_filepath = osp.join(syn_images_folder, 'debug/raw_bbox_%05d.txt' % i)
bbox_list = []
with open(bbox_filepath, "r") as file:
lines = file.readlines()
for line in lines:
classid, x, y, width, height, postr = line.split(',')
bbox_list.append([int(classid), float(x), float(y), float(width), float(height), float(postr[:-1])])
x = float(x)
y = float(y)
width = float(width)
height = float(height)
draw.rectangle([(x, y), (x + width, y + height)])
file.close()
bbox_list.sort(key=lambda obj: obj[5])
#Find occlusions and fix bounding boxes
covered_area = np.zeros((im.size[1],im.size[0],1), np.uint8)
after_occlusion_boxes = osp.join(syn_images_folder, 'bbox_%05d.txt' % i)
after_occlusion_file = open(after_occlusion_boxes,'a')
for k in range(len(bbox_list)-1,-1,-1):
mask_image = np.zeros((im.size[1],im.size[0],1), np.uint8)
mask_image[int(bbox_list[k][2]):int(bbox_list[k][2]+bbox_list[k][4]), int(bbox_list[k][1]):int(bbox_list[k][1]+bbox_list[k][3])] = 1
visible_area = cv2.bitwise_and(mask_image, cv2.bitwise_not(covered_area))
covered_area = cv2.bitwise_or(covered_area, mask_image)
contours, hierarchy = cv2.findContours(visible_area, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
maxcontourarea = 0
for c in range(0,len(contours)):
if (cv2.contourArea(contours[c]) > maxcontourarea):
maxcontourarea = cv2.contourArea(contours[c])
x1,y1,w1,h1 = cv2.boundingRect(contours[c])
if maxcontourarea > 50:
after_occlusion_file.write("%i, %i, %i, %i, %i\n" % (int(bbox_list[k][0] + 1), int(x1), int(y1), int(x1)+int(w1), int(y1)+int(h1)))
draw.rectangle([(x1, y1), (x1 + w1, y1 + h1)], outline=(255,0,0,255))
after_occlusion_file.close()
# save debug image showing bounding box correction
del draw
new_img_filepath = osp.join(syn_images_folder, 'debug/dbg_img_%05d.png' % i)
im.save(new_img_filepath)
def get_segmentation_labels(self, syn_images_folder, num_of_images):
for i in range(0, num_of_images):
img_filepath = osp.join(syn_images_folder, 'image_%05d.png' % i)
im = cv2.imread(img_filepath)
# Open a bounding box file, read all entry and sort in x-direction distance
bbox_filepath = osp.join(syn_images_folder, 'debug/raw_bbox_%05d.txt' % i)
bbox_list = []
with open(bbox_filepath, "r") as file:
lines = file.readlines()
for line in lines:
classid, x, y, width, height, postr = line.split(',')
bbox_list.append([int(classid), float(x), float(y), float(width), float(height), float(postr[:-1])])
file.close()
height, width, channels = im.shape
seg_img = np.zeros((height,width,1), np.uint8)
for k in range(0,len(bbox_list)):
mask_img_filepath = osp.join(syn_images_folder, 'debug/image_%05d_%02d.png' % (i,k))
mask_image = cv2.imread(mask_img_filepath)
for u in range(0, height):
for v in range(0,width):
if any(val != 64 for val in mask_image[u][v][:]):
seg_img[u][v] = np.uint8(bbox_list[k][0]+1)
os.remove(mask_img_filepath)
# save segmentation image
new_img_filepath = osp.join(syn_images_folder, 'seg_img_%05d.png' % i)
cv2.imwrite(new_img_filepath, seg_img)
# openCV does not have the functionality of saving indexed images
# lut = np.random.rand(256,1)
# dst_img = cv2.LUT(seg_img, lut)
# seg_img = cv2.applyColorMap(seg_img, cv2.COLORMAP_JET)
seg_img_plt = Image.open(new_img_filepath)
seg_img_plt.putpalette([
0, 0, 0,
128, 0, 0,
0, 128, 0,
128, 128, 0,
0, 128, 128,
128, 128, 128,
64, 0, 0,
192, 0, 0,
64, 128, 0,
192, 128, 0,
64, 0, 128,
192, 0, 128,
64, 128, 128,
192, 128, 128,
0, 64, 0,
128, 64, 0,
0, 192, 0,
128, 192, 0, # defined for 18 classes currently
])
seg_img_plt.save(new_img_filepath)