For chinese path in windows, use cv2.imdecode.

.gitignore

@@ -145,6 +145,7 @@ result/
 /pix2pix
 /pix2pixHD
 /tmp
+/tmp_files
 /to_make_show
 /test_media
 /result

cores/core.py

@@ -21,7 +21,7 @@ def addmosaic_img(opt,netS):
     img = impro.imread(path)
     mask = runmodel.get_ROI_position(img,netS,opt)[0]
     img = mosaic.addmosaic(img,mask,opt)
-    cv2.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_add.jpg'),img)
+    impro.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_add.jpg'),img)
 
 def addmosaic_video(opt,netS):
     path = opt.media_path
@@ -56,7 +56,7 @@ def styletransfer_img(opt,netG):
     img = impro.imread(opt.media_path)
     img = runmodel.run_styletransfer(opt, netG, img)
     suffix = os.path.basename(opt.model_path).replace('.pth','').replace('style_','')
-    cv2.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(opt.media_path))[0]+'_'+suffix+'.jpg'),img)
+    impro.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(opt.media_path))[0]+'_'+suffix+'.jpg'),img)
 
 def styletransfer_video(opt,netG):
     path = opt.media_path
@@ -89,7 +89,7 @@ def cleanmosaic_img(opt,netG,netM):
         img_result = impro.replace_mosaic(img_origin,img_fake,x,y,size,opt.no_feather)
     else:
         print('Do not find mosaic')
-    cv2.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_clean.jpg'),img_result)
+    impro.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_clean.jpg'),img_result)
 
 def cleanmosaic_video_byframe(opt,netG,netM):
     path = opt.media_path

cores/options.py

@@ -17,9 +17,9 @@ class Options():
         self.parser.add_argument('--model_path', type=str, default='./pretrained_models/add_hands_128.pth',help='pretrained model path')
         self.parser.add_argument('--result_dir', type=str, default='./result',help='output media will be saved here')
         self.parser.add_argument('--tempimage_type', type=str, default='png',help='type of temp image, png | jpg, png is better but occupy more storage space')
-        self.parser.add_argument('--output_size', type=int, default=0,help='size of output file,if 0 -> origin')
         self.parser.add_argument('--netG', type=str, default='auto',
-            help='select model to use for netG(Clean mosaic and Transfer style) -> auto | unet_128 | unet_256| resnet_9blocks | HD | video')
+            help='select model to use for netG(Clean mosaic and Transfer style) -> auto | unet_128 | unet_256 | resnet_9blocks | HD | video')
+        self.parser.add_argument('--output_size', type=int, default=0,help='size of output file,if 0 -> origin')
         
         #AddMosaic
         self.parser.add_argument('--mosaic_mod', type=str, default='squa_avg',help='type of mosaic -> squa_avg | squa_random | squa_avg_circle_edge | rect_avg | random')
@@ -35,7 +35,8 @@ class Options():
         self.parser.add_argument('--ex_mult', type=str, default='auto',help='mosaic area expansion')
         
         #StyleTransfer
-        self.parser.add_argument('--edges', action='store_true', help='if true, make edges first')
+        self.parser.add_argument('--preprocess', type=str, default='resize', help='resize and cropping of images at load time [ resize | resize_scale_width | edges | gray] or resize,edges(use comma to split)')
+        self.parser.add_argument('--edges', action='store_true', help='if true, use edges to generate pictures,(input_nc = 1)')  
         self.parser.add_argument('--canny', type=int, default=150,help='threshold of canny')
         self.parser.add_argument('--only_edges', action='store_true', help='if true, output media will be edges')
 
@@ -65,6 +66,12 @@ class Options():
             else:
                 print('Please input running mode!')
 
+        if self.opt.output_size == 0 and self.opt.mode == 'style':
+            self.opt.output_size = 512
+
+        if 'edges' in model_name or 'edges' in self.opt.preprocess:
+            self.opt.edges = True
+
         if self.opt.netG == 'auto' and self.opt.mode =='clean':
             if 'unet_128' in model_name:
                 self.opt.netG = 'unet_128'
@@ -77,12 +84,9 @@ class Options():
             else:
                 print('Type of Generator error!')
 
-        if 'edges' in model_name:
-            self.opt.edges = True
-
         if self.opt.ex_mult == 'auto':
             if 'face' in model_name:
-                self.opt.ex_mult = 1.2
+                self.opt.ex_mult = 1.1
             else:
                 self.opt.ex_mult = 1.5
         else:

deepmosaic.py

@@ -56,12 +56,12 @@ def main():
 
     util.clean_tempfiles(tmp_init = False)
         
-main()
-# if __name__ == '__main__':
-#     try:
-#         main()
-#     except Exception as e:
-#         print('Error:',e)
-#         input('Please press any key to exit.\n')
-#         util.clean_tempfiles(tmp_init = False)
-#         exit(0)
+# main()
+if __name__ == '__main__':
+    try:
+        main()
+    except Exception as e:
+        print('Error:',e)
+        input('Please press any key to exit.\n')
+        util.clean_tempfiles(tmp_init = False)
+        exit(0)

make_datasets/get_edges_pix2pix_dataset.py

+import numpy as np
+import cv2
+import os
+import sys
+sys.path.append("..")
+from util import image_processing as impro
+from util import util
+
+img_dir = './datasets_img/pix2pix/edges2cat/images'
+output_dir = './datasets_img/pix2pix/edges2cat/train'
+util.makedirs(output_dir)
+
+img_names = os.listdir(img_dir)
+for i,img_name in enumerate(img_names,2000): 
+    try:
+        img = impro.imread(os.path.join(img_dir,img_name))
+        img = impro.resize(img, 286)
+        h,w = img.shape[:2]
+        edges = cv2.Canny(img,150,250)
+        edges = impro.ch_one2three(edges)
+        out_img = np.zeros((h,w*2,3), dtype=np.uint8)
+        out_img[:,0:w] = edges
+        out_img[:,w:2*w] = img
+        cv2.imwrite(os.path.join(output_dir,'%05d' % i+'.jpg'), out_img)
+    except Exception as e:
+        pass

models/loadmodel.py

@@ -39,7 +39,7 @@ def pix2pix(opt):
 
 def style(opt):
     if opt.edges:
-        netG = define_G(1, 3, 64, 'unet_256', norm='instance',use_dropout=True, init_type='normal', gpu_ids=[])
+        netG = define_G(1, 3, 64, 'resnet_9blocks', norm='instance',use_dropout=True, init_type='normal', gpu_ids=[])
     else:
         netG = define_G(3, 3, 64, 'resnet_9blocks', norm='instance',use_dropout=False, init_type='normal', gpu_ids=[])
 

models/runmodel.py

@@ -37,11 +37,15 @@ def run_pix2pix(img,net,opt):
     return img_fake
 
 def run_styletransfer(opt, net, img):
+
     if opt.output_size != 0:
-        img = impro.resize(img,opt.output_size)
-    if opt.edges:
-        if not opt.only_edges:
-            img = img[0:256*int(img.shape[0]/256),0:256*int(img.shape[1]/256),:]
+        if 'resize' in opt.preprocess and 'resize_scale_width' not in opt.preprocess:
+            img = impro.resize(img,opt.output_size)
+        elif 'resize_scale_width' in opt.preprocess:
+            img = cv2.resize(img, (opt.output_size,opt.output_size))
+        img = img[0:4*int(img.shape[0]/4),0:4*int(img.shape[1]/4),:]
+
+    if 'edges' in opt.preprocess:
         if opt.canny > 100:
             canny_low = opt.canny-50
             canny_high = np.clip(opt.canny+50,0,255)
@@ -56,7 +60,6 @@ def run_styletransfer(opt, net, img):
             return img
         img = data.im2tensor(img,use_gpu=opt.use_gpu,gray=True,use_transform = False,is0_1 = False)
     else:    
-        img = img[0:4*int(img.shape[0]/4),0:4*int(img.shape[1]/4),:]
         img = data.im2tensor(img,use_gpu=opt.use_gpu)
     img = net(img)
     img = data.tensor2im(img)

util/ffmpeg.py

@@ -45,4 +45,4 @@ def continuous_screenshot(videopath,savedir,fps):
     fps:       save how many images per second
     '''
     videoname = os.path.splitext(os.path.basename(videopath))[0]
-    os.system('ffmpeg -i '+videopath+' -vf fps='+str(fps)+' '+savedir+'/'+videoname+'_%05d.jpg')
+    os.system('ffmpeg -i "'+videopath+'" -vf fps='+str(fps)+' '+savedir+'/'+videoname+'_%05d.jpg')

util/image_processing.py

@@ -2,20 +2,42 @@ import cv2
 import numpy as np
 import random
 
+import platform
+system_type = 'Linux'
+if 'Windows' in platform.platform():
+    system_type = 'Windows'
+
 def imread(file_path,mod = 'normal'):
     '''
     mod = 'normal' | 'gray' | 'all'
     '''
-    if mod == 'normal':
-        cv_img = cv2.imread(file_path)
-    elif mod == 'gray':
-        cv_img = cv2.imread(file_path,0)
-    elif mod == 'all':
-        cv_img = cv2.imread(file_path,-1)
-
-    # # imread for chinese path in windows but no EXIF
-    # cv_img = cv2.imdecode(np.fromfile(file_path,dtype=np.uint8),-1)
-    return cv_img
+    if system_type == 'Linux':
+        if mod == 'normal':
+            img = cv2.imread(file_path)
+        elif mod == 'gray':
+            img = cv2.imread(file_path,0)
+        elif mod == 'all':
+            img = cv2.imread(file_path,-1)
+    
+    #For chinese path, use cv2.imdecode in windows.
+    #It will loss EXIF, I can't fix it
+    else: 
+        if mod == 'gray':
+            img = cv2.imdecode(np.fromfile(file_path,dtype=np.uint8),0)
+        else:
+            img = cv2.imdecode(np.fromfile(file_path,dtype=np.uint8),-1)
+
+    return img
+
+def imwrite(file_path,img):
+    '''
+    in other to save chinese path images in windows,
+    this fun just for save final output images
+    '''
+    if system_type == 'Linux':
+        cv2.imwrite(file_path, img)
+    else:
+        cv2.imencode('.jpg', img)[1].tofile(file_path)
 
 def resize(img,size,interpolation=cv2.INTER_LINEAR):
     h, w = img.shape[:2]