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Runtime error
| import os | |
| import requests | |
| import random | |
| import _thread as thread | |
| from uuid import uuid4 | |
| import urllib | |
| import numpy as np | |
| import skimage | |
| from skimage.filters import gaussian | |
| from PIL import Image | |
| def compress_image(image, path_original): | |
| size = 1920, 1080 | |
| width = 1920 | |
| height = 1080 | |
| name = os.path.basename(path_original).split('.') | |
| first_name = os.path.join(os.path.dirname(path_original), name[0] + '.jpg') | |
| if image.size[0] > width and image.size[1] > height: | |
| image.thumbnail(size, Image.ANTIALIAS) | |
| image.save(first_name, quality=85) | |
| elif image.size[0] > width: | |
| wpercent = (width/float(image.size[0])) | |
| height = int((float(image.size[1])*float(wpercent))) | |
| image = image.resize((width,height), Image.ANTIALIAS) | |
| image.save(first_name,quality=85) | |
| elif image.size[1] > height: | |
| wpercent = (height/float(image.size[1])) | |
| width = int((float(image.size[0])*float(wpercent))) | |
| image = image.resize((width,height), Image.ANTIALIAS) | |
| image.save(first_name, quality=85) | |
| else: | |
| image.save(first_name, quality=85) | |
| def convertToJPG(path_original): | |
| img = Image.open(path_original) | |
| name = os.path.basename(path_original).split('.') | |
| first_name = os.path.join(os.path.dirname(path_original), name[0] + '.jpg') | |
| if img.format == "JPEG": | |
| image = img.convert('RGB') | |
| compress_image(image, path_original) | |
| img.close() | |
| elif img.format == "GIF": | |
| i = img.convert("RGBA") | |
| bg = Image.new("RGBA", i.size) | |
| image = Image.composite(i, bg, i) | |
| compress_image(image, path_original) | |
| img.close() | |
| elif img.format == "PNG": | |
| try: | |
| image = Image.new("RGB", img.size, (255,255,255)) | |
| image.paste(img,img) | |
| compress_image(image, path_original) | |
| except ValueError: | |
| image = img.convert('RGB') | |
| compress_image(image, path_original) | |
| img.close() | |
| elif img.format == "BMP": | |
| image = img.convert('RGB') | |
| compress_image(image, path_original) | |
| img.close() | |
| def blur(image, x0, x1, y0, y1, sigma=1, multichannel=True): | |
| y0, y1 = min(y0, y1), max(y0, y1) | |
| x0, x1 = min(x0, x1), max(x0, x1) | |
| im = image.copy() | |
| sub_im = im[y0:y1,x0:x1].copy() | |
| blur_sub_im = gaussian(sub_im, sigma=sigma, multichannel=multichannel) | |
| blur_sub_im = np.round(255 * blur_sub_im) | |
| im[y0:y1,x0:x1] = blur_sub_im | |
| return im | |
| def download(url, filename): | |
| data = requests.get(url).content | |
| with open(filename, 'wb') as handler: | |
| handler.write(data) | |
| return filename | |
| def generate_random_filename(upload_directory, extension): | |
| filename = str(uuid4()) | |
| filename = os.path.join(upload_directory, filename + "." + extension) | |
| return filename | |
| def clean_me(filename): | |
| if os.path.exists(filename): | |
| os.remove(filename) | |
| def clean_all(files): | |
| for me in files: | |
| clean_me(me) | |
| def create_directory(path): | |
| os.makedirs(os.path.dirname(path), exist_ok=True) | |
| def get_model_bin(url, output_path): | |
| # print('Getting model dir: ', output_path) | |
| if not os.path.exists(output_path): | |
| create_directory(output_path) | |
| urllib.request.urlretrieve(url, output_path) | |
| # cmd = "wget -O %s %s" % (output_path, url) | |
| # print(cmd) | |
| # os.system(cmd) | |
| return output_path | |
| #model_list = [(url, output_path), (url, output_path)] | |
| def get_multi_model_bin(model_list): | |
| for m in model_list: | |
| thread.start_new_thread(get_model_bin, m) | |