xuzuoyun 3 yıl önce
ebeveyn
işleme
d563fbc0f2
2 değiştirilmiş dosya ile 39 ekleme ve 39 silme
  1. BIN
      __pycache__/main.cpython-36.pyc
  2. 39 39
      main.py

BIN
__pycache__/main.cpython-36.pyc


+ 39 - 39
main.py

@@ -245,49 +245,49 @@ def videoSwap(opt):
     task.status = 'processing'
     task.start_time =  datetime.now()
     update(task)
-    # try:
-    start_epoch, epoch_iter = 1, 0
-    crop_size = 224
-    # opt_dict = vars(opt)
-    # args = get_args_from_json(item,opt_dict)
-    torch.nn.Module.dump_patches = True
-    model = create_model(opt)
-    model.eval()
-    app = Face_detect_crop(name='antelope', root='./insightface_func/models')
-    app.prepare(ctx_id= 0, det_thresh=0.6, det_size=(640,640))
-    
-    with torch.no_grad():
-        pic_a = opt.pic_a_path
-        # img_a = Image.open(pic_a).convert('RGB')
-        img_a_whole = cv2.imread(pic_a)
-        img_a_align_crop, _ = app.get(img_a_whole,crop_size)
-        img_a_align_crop_pil = Image.fromarray(cv2.cvtColor(img_a_align_crop[0],cv2.COLOR_BGR2RGB)) 
-        img_a = transformer_Arcface(img_a_align_crop_pil)
-        img_id = img_a.view(-1, img_a.shape[0], img_a.shape[1], img_a.shape[2])
+    try:
+        start_epoch, epoch_iter = 1, 0
+        crop_size = 224
+        # opt_dict = vars(opt)
+        # args = get_args_from_json(item,opt_dict)
+        torch.nn.Module.dump_patches = True
+        model = create_model(opt)
+        model.eval()
+        app = Face_detect_crop(name='antelope', root='./insightface_func/models')
+        app.prepare(ctx_id= 0, det_thresh=0.6, det_size=(640,640))
+        
+        with torch.no_grad():
+            pic_a = opt.pic_a_path
+            # img_a = Image.open(pic_a).convert('RGB')
+            img_a_whole = cv2.imread(pic_a)
+            img_a_align_crop, _ = app.get(img_a_whole,crop_size)
+            img_a_align_crop_pil = Image.fromarray(cv2.cvtColor(img_a_align_crop[0],cv2.COLOR_BGR2RGB)) 
+            img_a = transformer_Arcface(img_a_align_crop_pil)
+            img_id = img_a.view(-1, img_a.shape[0], img_a.shape[1], img_a.shape[2])
 
-        # pic_b = opt.pic_b_path
-        # img_b_whole = cv2.imread(pic_b)
-        # img_b_align_crop, b_mat = app.get(img_b_whole,crop_size)
-        # img_b_align_crop_pil = Image.fromarray(cv2.cvtColor(img_b_align_crop,cv2.COLOR_BGR2RGB)) 
-        # img_b = transformer(img_b_align_crop_pil)
-        # img_att = img_b.view(-1, img_b.shape[0], img_b.shape[1], img_b.shape[2])
+            # pic_b = opt.pic_b_path
+            # img_b_whole = cv2.imread(pic_b)
+            # img_b_align_crop, b_mat = app.get(img_b_whole,crop_size)
+            # img_b_align_crop_pil = Image.fromarray(cv2.cvtColor(img_b_align_crop,cv2.COLOR_BGR2RGB)) 
+            # img_b = transformer(img_b_align_crop_pil)
+            # img_att = img_b.view(-1, img_b.shape[0], img_b.shape[1], img_b.shape[2])
 
-        # convert numpy to tensor
-        img_id = img_id.cuda()
-        # img_att = img_att.cuda()
+            # convert numpy to tensor
+            img_id = img_id.cuda()
+            # img_att = img_att.cuda()
 
-        #create latent id
-        img_id_downsample = F.interpolate(img_id, scale_factor=0.5)
-        latend_id = model.netArc(img_id_downsample)
-        latend_id = F.normalize(latend_id, p=2, dim=1)
+            #create latent id
+            img_id_downsample = F.interpolate(img_id, scale_factor=0.5)
+            latend_id = model.netArc(img_id_downsample)
+            latend_id = F.normalize(latend_id, p=2, dim=1)
 
-        video_swap(opt.video_path, latend_id, model, app, opt.output_path,temp_results_dir=opt.temp_path,\
-            no_simswaplogo=opt.no_simswaplogo,use_mask=opt.use_mask)
-    # except:
-    #     task = query(opt.taskId,None,None,None)[0]
-    #     task.status = 'process_error'
-    #     update(task)
-    #     del_file(opt.base_path)
+            video_swap(opt.video_path, latend_id, model, app, opt.output_path,temp_results_dir=opt.temp_path,\
+                no_simswaplogo=opt.no_simswaplogo,use_mask=opt.use_mask)
+    except:
+        task = query(opt.taskId,None,None,None)[0]
+        task.status = 'process_error'
+        update(task)
+        del_file(opt.base_path)
     output_video_md5 = getmd5(opt.output_path)
     task = query(opt.taskId,None,None,None)[0]
     task.status = 'uploading'