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crop_plates.py
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crop_plates.py
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#!/usr/bin/python
import os
import sys
import json
import math
import cv, cv2
import numpy as np
import copy
import yaml
from argparse import ArgumentParser
parser = ArgumentParser(description='OpenALPR License Plate Cropper')
parser.add_argument( "--input_dir", dest="input_dir", action="store", type=str, required=True,
help="Directory containing plate images and yaml metadata" )
parser.add_argument( "--out_dir", dest="out_dir", action="store", type=str, required=True,
help="Directory to output cropped plates" )
parser.add_argument( "--zoom_out_percent", dest="zoom_out_percent", action="store", type=float, default=1.25,
help="Percent multiplier to zoom out before cropping" )
parser.add_argument( "--plate_width", dest="plate_width", action="store", type=float, required=True,
help="Desired aspect ratio width" )
parser.add_argument( "--plate_height", dest="plate_height", action="store", type=float, required=True,
help="Desired aspect ratio height" )
options = parser.parse_args()
if not os.path.isdir(options.input_dir):
print "input_dir (%s) doesn't exist"
sys.exit(1)
if not os.path.isdir(options.out_dir):
os.makedirs(options.out_dir)
def get_box(x1, y1, x2, y2, x3, y3, x4, y4):
height1 = int(round(math.sqrt((x1-x4)*(x1-x4) + (y1-y4)*(y1-y4))))
height2 = int(round(math.sqrt((x3-x2)*(x3-x2) + (y3-y2)*(y3-y2))))
height = height1
if height2 > height:
height = height2
# add 25% to the height
height *= options.zoom_out_percent
#height += (height * .05)
#print "Height: %d - %d" % (height1, height2)
points = [(x1,y1), (x2,y2), (x3,y3), (x4,y4)]
moment = cv.Moments(points)
centerx = int(round(moment.m10/moment.m00))
centery = int(round(moment.m01/moment.m00))
training_aspect = options.plate_width / options.plate_height
width = int(round(training_aspect * height))
# top_left = ( int(centerx - (width / 2)), int(centery - (height / 2)))
# bottom_right = ( int(centerx + (width / 2)), int(centery + (height / 2)))
top_left_x = int(round(centerx - (width / 2)))
top_left_y = int(round(centery - (height / 2)))
return (top_left_x, top_left_y, width, int(round(height)))
def crop_rect(big_image, x,y,width,height):
# Crops the rectangle from the big image and returns a cropped image
# Special care is taken to avoid cropping beyond the edge of the image.
# It fills this area in with random pixels
(big_height, big_width, channels) = big_image.shape
if x >= 0 and y >= 0 and (y+height) < big_height and (x+width) < big_width:
crop_img = img[y:y+height, x:x+width]
else:
#print "Performing partial crop"
#print "x: %d y: %d width: %d height: %d" % (x,y,width,height)
#print "big_width: %d big_height: %d" % (big_width, big_height)
crop_img = np.zeros((height, width, 3), np.uint8)
cv2.randu(crop_img, (0,0,0), (255,255,255))
offset_x = 0
offset_y = 0
if x < 0:
offset_x = -1 * x
x = 0
width -= offset_x
if y < 0:
offset_y = -1 * y
y = 0
height -= offset_y
if (x+width) >= big_width:
offset_x = 0
width = big_width - x
if (y+height) >= big_height:
offset_y = 0
height = big_height - y
#print "offset_x: %d offset_y: %d, width: %d, height: %d" % (offset_x, offset_y, width, height)
original_crop = img[y:y+height-1, x:x+width-1]
(small_image_height, small_image_width, channels) = original_crop.shape
#print "Small shape: %dx%d" % (small_image_width, small_image_height)
# Draw the small image onto the large image
crop_img[offset_y:offset_y+small_image_height, offset_x:offset_x+small_image_width] = original_crop
#cv2.imshow("Test", crop_img)
return crop_img
count = 1
yaml_files = []
for in_file in os.listdir(options.input_dir):
if in_file.endswith('.yaml') or in_file.endswith('.yml'):
yaml_files.append(in_file)
yaml_files.sort()
for yaml_file in yaml_files:
print "Processing: " + yaml_file + " (" + str(count) + "/" + str(len(yaml_files)) + ")"
count += 1
yaml_path = os.path.join(options.input_dir, yaml_file)
yaml_without_ext = os.path.splitext(yaml_path)[0]
with open(yaml_path, 'r') as yf:
yaml_obj = yaml.load(yf)
image = yaml_obj['image_file']
# Skip missing images
full_image_path = os.path.join(options.input_dir, image)
if not os.path.isfile(full_image_path):
print "Could not find image file %s, skipping" % (full_image_path)
continue
plate_corners = yaml_obj['plate_corners_gt']
cc = plate_corners.strip().split()
for i in range(0, len(cc)):
cc[i] = int(cc[i])
box = get_box(cc[0], cc[1], cc[2], cc[3], cc[4], cc[5], cc[6], cc[7])
img = cv2.imread(full_image_path)
crop = crop_rect(img, box[0], box[1], box[2], box[3])
# cv2.imshow("test", crop)
# cv2.waitKey(0)
out_crop_path = os.path.join(options.out_dir, yaml_without_ext + ".jpg")
cv2.imwrite(out_crop_path, crop )
print "%d Cropped images are located in %s" % (count-1, options.out_dir)