Merge pull request #16 from LielinJiang/adapt-to-2.0-api

Adapt to api 2.0 again

Author: LielinJiang

applications/DAIN/predict.py

@@ -11,14 +11,15 @@
 import cv2
 
 import paddle.fluid as fluid
-from paddle.incubate.hapi.download import get_path_from_url
+from paddle.utils.download import get_path_from_url
 
 import networks
 from util import *
 from my_args import parser
 
 DAIN_WEIGHT_URL = 'https://paddlegan.bj.bcebos.com/applications/DAIN_weight.tar'
 
+
 def infer_engine(model_dir,
                  run_mode='fluid',
                  batch_size=1,
@@ -91,7 +92,6 @@ def __init__(self,
         self.exe, self.program, self.fetch_targets = executor(model_path,
                                                               use_gpu=use_gpu)
 
-
     def run(self):
         frame_path_input = os.path.join(self.output_path, 'frames-input')
         frame_path_interpolated = os.path.join(self.output_path,
@@ -272,7 +272,7 @@ def run(self):
                 os.remove(video_pattern_output)
             frames_to_video_ffmpeg(frame_pattern_combined, video_pattern_output,
                                    r2)
-            
+
         return frame_pattern_combined, video_pattern_output
 
 

applications/DeOldify/predict.py

@@ -15,15 +15,19 @@
 from tqdm import tqdm
 from paddle import fluid
 from model import build_model
-from paddle.incubate.hapi.download import get_path_from_url
+from paddle.utils.download import get_path_from_url
 
 parser = argparse.ArgumentParser(description='DeOldify')
-parser.add_argument('--input',   type=str,   default='none', help='Input video')
-parser.add_argument('--output',   type=str,   default='output', help='output dir')
-parser.add_argument('--weight_path',  type=str, default='none', help='Path to the reference image directory')
+parser.add_argument('--input', type=str, default='none', help='Input video')
+parser.add_argument('--output', type=str, default='output', help='output dir')
+parser.add_argument('--weight_path',
+                    type=str,
+                    default='none',
+                    help='Path to the reference image directory')
 
 DeOldify_weight_url = 'https://paddlegan.bj.bcebos.com/applications/DeOldify_stable.pdparams'
 
+
 def frames_to_video_ffmpeg(framepath, videopath, r):
     ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
     cmd = ffmpeg + [
@@ -56,9 +60,9 @@ def __init__(self, input, output, batch_size=1, weight_path=None):
     def norm(self, img, render_factor=32, render_base=16):
         target_size = render_factor * render_base
         img = img.resize((target_size, target_size), resample=Image.BILINEAR)
-        
+
         img = np.array(img).transpose([2, 0, 1]).astype('float32') / 255.0
-        
+
         img_mean = np.array([0.485, 0.456, 0.406]).reshape((3, 1, 1))
         img_std = np.array([0.229, 0.224, 0.225]).reshape((3, 1, 1))
 
@@ -69,13 +73,13 @@ def norm(self, img, render_factor=32, render_base=16):
     def denorm(self, img):
         img_mean = np.array([0.485, 0.456, 0.406]).reshape((3, 1, 1))
         img_std = np.array([0.229, 0.224, 0.225]).reshape((3, 1, 1))
-        
+
         img *= img_std
         img += img_mean
         img = img.transpose((1, 2, 0))
 
         return (img * 255).clip(0, 255).astype('uint8')
-    
+
     def post_process(self, raw_color, orig):
         color_np = np.asarray(raw_color)
         orig_np = np.asarray(orig)
@@ -86,11 +90,11 @@ def post_process(self, raw_color, orig):
         final = cv2.cvtColor(hires, cv2.COLOR_YUV2BGR)
         final = Image.fromarray(final)
         return final
-        
+
     def run_single(self, img_path):
         ori_img = Image.open(img_path).convert('LA').convert('RGB')
         img = self.norm(ori_img)
-        x = paddle.to_tensor(img[np.newaxis,...])
+        x = paddle.to_tensor(img[np.newaxis, ...])
         out = self.model(x)
 
         pred_img = self.denorm(out.numpy()[0])
@@ -118,20 +122,20 @@ def run(self):
 
         frames = sorted(glob.glob(os.path.join(out_path, '*.png')))
 
-
         for frame in tqdm(frames):
             pred_img = self.run_single(frame)
 
             frame_name = os.path.basename(frame)
             pred_img.save(os.path.join(pred_frame_path, frame_name))
-        
+
         frame_pattern_combined = os.path.join(pred_frame_path, '%08d.png')
-        
-        vid_out_path = os.path.join(output_path, '{}_deoldify_out.mp4'.format(base_name))
-        frames_to_video_ffmpeg(frame_pattern_combined, vid_out_path, str(int(fps)))
 
-        return frame_pattern_combined, vid_out_path
+        vid_out_path = os.path.join(output_path,
+                                    '{}_deoldify_out.mp4'.format(base_name))
+        frames_to_video_ffmpeg(frame_pattern_combined, vid_out_path,
+                               str(int(fps)))
 
+        return frame_pattern_combined, vid_out_path
 
 
 def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
@@ -147,21 +151,8 @@ def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
 
     if ss is not None and t is not None and r is not None:
         cmd = ffmpeg + [
-            ' -ss ',
-            ss,
-            ' -t ',
-            t,
-            ' -i ',
-            vid_path,
-            ' -r ',
-            r,
-
-            ' -qscale:v ',
-            ' 0.1 ',
-            ' -start_number ',
-            ' 0 ',
-
-            outformat
+            ' -ss ', ss, ' -t ', t, ' -i ', vid_path, ' -r ', r, ' -qscale:v ',
+            ' 0.1 ', ' -start_number ', ' 0 ', outformat
         ]
     else:
         cmd = ffmpeg + [' -i ', vid_path, ' -start_number ', ' 0 ', outformat]
@@ -177,11 +168,13 @@ def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
     return out_full_path
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     paddle.enable_imperative()
     args = parser.parse_args()
 
-    predictor = DeOldifyPredictor(args.input, args.output, weight_path=args.weight_path)
+    predictor = DeOldifyPredictor(args.input,
+                                  args.output,
+                                  weight_path=args.weight_path)
     frames_path, temp_video_path = predictor.run()
 
-    print('output video path:', temp_video_path)
+    print('output video path:', temp_video_path)