Fix training part #5

cores/options.py

@@ -50,7 +50,7 @@ class Options():
         self.initialized = True
 
 
-    def getparse(self):
+    def getparse(self, test_flag = False):
         if not self.initialized:
             self.initialize()
         self.opt = self.parser.parse_args()
@@ -65,10 +65,11 @@ class Options():
         else:
             self.opt.use_gpu = -1
 
-        if not os.path.exists(self.opt.media_path):
-            print('Error: Bad media path!')
-            input('Please press any key to exit.\n')
-            exit(0)
+        if test_flag:
+            if not os.path.exists(self.opt.media_path):
+                print('Error: Bad media path!')
+                input('Please press any key to exit.\n')
+                exit(0)
 
         if self.opt.mode == 'auto':
             if 'clean' in model_name or self.opt.traditional:

deepmosaic.py

@@ -5,7 +5,7 @@ from cores import Options,core
 from util import util
 from models import loadmodel
 
-opt = Options().getparse()
+opt = Options().getparse(test_flag = True)
 util.file_init(opt)
 
 def main():

make_datasets/make_pix2pix_dataset.py

@@ -106,7 +106,13 @@ for fold in range(opt.fold):
                 # t.start()
 
                 saveflag = True
-                x,y,size,area = impro.boundingSquare(mask, random.uniform(1.4,1.6))
+                if opt.mod == ['drawn','irregular']:
+                    x,y,size,area = impro.boundingSquare(mask_drawn, random.uniform(1.2,1.6))
+                elif opt.mod == ['network','irregular']:
+                    x,y,size,area = impro.boundingSquare(mask_net, random.uniform(1.2,1.6))
+                else:
+                    x,y,size,area = impro.boundingSquare(mask, random.uniform(1.2,1.6))
+
                 if area < 1000:
                     saveflag = False
                 else:

train/add/train.py

@@ -10,6 +10,8 @@ import datetime
 import time
 
 import numpy as np
+import matplotlib
+matplotlib.use('Agg')
 from matplotlib import pyplot as plt
 import cv2
 

train/clean/train.py

@@ -16,6 +16,8 @@ from multiprocessing import Process, Queue
 from util import mosaic,util,ffmpeg,filt,data
 from util import image_processing as impro
 from models import pix2pix_model,pix2pixHD_model,video_model,unet_model,loadmodel,videoHD_model
+import matplotlib
+matplotlib.use('Agg')
 from matplotlib import pyplot as plt
 import torch.backends.cudnn as cudnn
 

util/image_processing.py

@@ -79,7 +79,7 @@ def ch_one2three(img):
     res = cv2.merge([img, img, img])
     return res
 
-def color_adjust(img,alpha=1,beta=0,b=0,g=0,r=0,ran = False):
+def color_adjust(img,alpha=0,beta=0,b=0,g=0,r=0,ran = False):
     '''
     g(x) = (1+α)g(x)+255*β, 
     g(x) = g(x[:+b*255,:+g*255,:+r*255])