Merge pull request #21 from LielinJiang/refine-code

Refine application code

applications/DAIN/predict.py

@@ -8,6 +8,7 @@
 import glob
 import numpy as np
 from imageio import imread, imsave
+from tqdm import tqdm
 import cv2
 
 import paddle.fluid as fluid
@@ -175,8 +176,7 @@ def run(self):
             if not os.path.exists(os.path.join(frame_path_combined, vidname)):
                 os.makedirs(os.path.join(frame_path_combined, vidname))
 
-            for i in range(frame_num - 1):
-                print(frames[i])
+            for i in tqdm(range(frame_num - 1)):
                 first = frames[i]
                 second = frames[i + 1]
 
@@ -208,12 +208,10 @@ def run(self):
                     assert (X0.shape[1] == X1.shape[1])
                     assert (X0.shape[2] == X1.shape[2])
 
-                    print("size before padding ", X0.shape)
                     X0 = np.pad(X0, ((0,0), (padding_top, padding_bottom), \
                         (padding_left, padding_right)), mode='edge')
                     X1 = np.pad(X1, ((0,0), (padding_top, padding_bottom), \
                         (padding_left, padding_right)), mode='edge')
-                    print("size after padding ", X0.shape)
 
                     X0 = np.expand_dims(X0, axis=0)
                     X1 = np.expand_dims(X1, axis=0)
@@ -233,8 +231,6 @@ def run(self):
                     proc_timer.update(time.time() - proc_end)
                     tot_timer.update(time.time() - end)
                     end = time.time()
-                    print("*********** current image process time \t " +
-                          str(time.time() - proc_end) + "s *********")
 
                     y_ = [
                         np.transpose(

applications/DAIN/util.py

@@ -22,7 +22,7 @@ def update(self, val, n=1):
 
 
 def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     vid_name = vid_path.split('/')[-1].split('.')[0]
     out_full_path = os.path.join(outpath, vid_name)
 
@@ -66,7 +66,7 @@ def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
 
 
 def frames_to_video_ffmpeg(framepath, videopath, r):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     cmd = ffmpeg + [
         ' -r ', r, ' -f ', ' image2 ', ' -i ', framepath, ' -vcodec ',
         ' libx264 ', ' -pix_fmt ', ' yuv420p ', ' -crf ', ' 16 ', videopath
@@ -99,7 +99,8 @@ def combine_frames(input, interpolated, combined, num_frames):
                 for k in range(num_frames):
                     src = frames2[i * num_frames + k]
                     dst = os.path.join(
-                        combined, '{:08d}.png'.format(i * (num_frames + 1) + k + 1))
+                        combined,
+                        '{:08d}.png'.format(i * (num_frames + 1) + k + 1))
                     shutil.copy2(src, dst)
             except Exception as e:
                 print(e)

applications/DeOldify/model.py

@@ -147,10 +147,8 @@ def custom_conv_layer(ni: int,
                      stride=stride,
                      padding=padding)
     if norm_type == 'Weight':
-        print('use weight norm')
         conv = nn.utils.weight_norm(conv)
     elif norm_type == 'Spectral':
-        # pass
         conv = Spectralnorm(conv)
     layers = [conv]
     if use_activ:

applications/DeOldify/predict.py

@@ -29,7 +29,7 @@
 
 
 def frames_to_video_ffmpeg(framepath, videopath, r):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     cmd = ffmpeg + [
         ' -r ', r, ' -f ', ' image2 ', ' -i ', framepath, ' -vcodec ',
         ' libx264 ', ' -pix_fmt ', ' yuv420p ', ' -crf ', ' 16 ', videopath
@@ -139,7 +139,7 @@ def run(self):
 
 
 def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     vid_name = vid_path.split('/')[-1].split('.')[0]
     out_full_path = os.path.join(outpath, 'frames_input')
 
@@ -169,7 +169,7 @@ def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
 
 
 if __name__ == '__main__':
-    paddle.enable_imperative()
+    paddle.disable_static()
     args = parser.parse_args()
 
     predictor = DeOldifyPredictor(args.input,

applications/EDVR/data.py

@@ -2,19 +2,20 @@
 
 import numpy as np
 
+
 def read_img(path, size=None, is_gt=False):
     """read image by cv2
     return: Numpy float32, HWC, BGR, [0,1]"""
-    # print('debug:', path)
     img = cv2.imread(path, cv2.IMREAD_UNCHANGED)
-    
+
     img = img.astype(np.float32) / 255.
     if img.ndim == 2:
         img = np.expand_dims(img, axis=2)
-    
+
     if img.shape[2] > 3:
-        img = img[:, :, :3] 
-    return img 
+        img = img[:, :, :3]
+    return img
+
 
 def get_test_neighbor_frames(crt_i, N, max_n, padding='new_info'):
     """Generate an index list for reading N frames from a sequence of images
@@ -62,15 +63,14 @@ def get_test_neighbor_frames(crt_i, N, max_n, padding='new_info'):
         else:
             add_idx = i
         return_l.append(add_idx)
-    # name_b = '{:08d}'.format(crt_i)    
+    # name_b = '{:08d}'.format(crt_i)
     return return_l
 
 
 class EDVRDataset:
     def __init__(self, frame_paths):
         self.frames = frame_paths
 
-
     def __getitem__(self, index):
         indexs = get_test_neighbor_frames(index, 5, len(self.frames))
         frame_list = []
@@ -79,12 +79,11 @@ def __getitem__(self, index):
             frame_list.append(img)
 
         img_LQs = np.stack(frame_list, axis=0)
-        print('img:', img_LQs.shape)
         # BGR to RGB, HWC to CHW, numpy to tensor
         img_LQs = img_LQs[:, :, :, [2, 1, 0]]
         img_LQs = np.transpose(img_LQs, (0, 3, 1, 2)).astype('float32')
 
         return img_LQs, self.frames[index]
 
     def __len__(self):
-        return len(self.frames)
+        return len(self.frames)

applications/EDVR/predict.py

@@ -27,6 +27,7 @@
 import paddle.fluid as fluid
 import cv2
 
+from tqdm import tqdm
 from data import EDVRDataset
 from paddle.utils.download import get_path_from_url
 
@@ -52,7 +53,6 @@ def parse_args():
 
 
 def get_img(pred):
-    print('pred shape', pred.shape)
     pred = pred.squeeze()
     pred = np.clip(pred, a_min=0., a_max=1.0)
     pred = pred * 255
@@ -72,7 +72,7 @@ def save_img(img, framename):
 
 
 def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     vid_name = vid_path.split('/')[-1].split('.')[0]
     out_full_path = os.path.join(outpath, 'frames_input')
 
@@ -102,7 +102,7 @@ def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
 
 
 def frames_to_video_ffmpeg(framepath, videopath, r):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     cmd = ffmpeg + [
         ' -r ', r, ' -f ', ' image2 ', ' -i ', framepath, ' -vcodec ',
         ' libx264 ', ' -pix_fmt ', ' yuv420p ', ' -crf ', ' 16 ', videopath
@@ -164,7 +164,7 @@ def run(self):
 
         periods = []
         cur_time = time.time()
-        for infer_iter, data in enumerate(dataset):
+        for infer_iter, data in enumerate(tqdm(dataset)):
             data_feed_in = [data[0]]
 
             infer_outs = self.exe.run(
@@ -185,7 +185,7 @@ def run(self):
             period = cur_time - prev_time
             periods.append(period)
 
-            print('Processed {} samples'.format(infer_iter + 1))
+            # print('Processed {} samples'.format(infer_iter + 1))
         frame_pattern_combined = os.path.join(pred_frame_path, '%08d.png')
         vid_out_path = os.path.join(self.output,
                                     '{}_edvr_out.mp4'.format(base_name))

applications/RealSR/predict.py

@@ -28,7 +28,7 @@
 
 
 def frames_to_video_ffmpeg(framepath, videopath, r):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     cmd = ffmpeg + [
         ' -r ', r, ' -f ', ' image2 ', ' -i ', framepath, ' -vcodec ',
         ' libx264 ', ' -pix_fmt ', ' yuv420p ', ' -crf ', ' 16 ', videopath
@@ -110,7 +110,7 @@ def run(self):
 
 
 def dump_frames_ffmpeg(vid_path, outpath, r=None, ss=None, t=None):
-    ffmpeg = ['ffmpeg ', ' -loglevel ', ' error ']
+    ffmpeg = ['ffmpeg ', ' -y -loglevel ', ' error ']
     vid_name = vid_path.split('/')[-1].split('.')[0]
     out_full_path = os.path.join(outpath, 'frames_input')