Update gradio_app.py

gradio_app.py

@@ -28,6 +28,36 @@ from huggingface_hub import snapshot_download
 import os
 
 
+def download_model():
+    REPO_ID = 'Doubiiu/ToonCrafter'
+    filename_list = ['model.ckpt']
+    if not os.path.exists('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/'):
+        os.makedirs('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/')
+    for filename in filename_list:
+        local_file = os.path.join('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/', filename)
+        if not os.path.exists(local_file):
+            hf_hub_download(repo_id=REPO_ID, filename=filename, local_dir='./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/', local_dir_use_symlinks=False)
+    print("downloaded")
+    
+
+def get_latent_z_with_hidden_states(model, videos):
+    b, c, t, h, w = videos.shape
+    x = rearrange(videos, 'b c t h w -> (b t) c h w')
+    encoder_posterior, hidden_states = model.first_stage_model.encode(x, return_hidden_states=True)
+
+    hidden_states_first_last = []
+    ### use only the first and last hidden states
+    for hid in hidden_states:
+        hid = rearrange(hid, '(b t) c h w -> b c t h w', t=t)
+        hid_new = torch.cat([hid[:, :, 0:1], hid[:, :, -1:]], dim=2)
+        hidden_states_first_last.append(hid_new)
+
+    z = model.get_first_stage_encoding(encoder_posterior).detach()
+    z = rearrange(z, '(b t) c h w -> b c t h w', b=b, t=t)
+    return z, hidden_states_first_last
+
+
+
 def extract_frames(video_path):
     # 動画ファイルを読み込む
     cap = cv2.VideoCapture(video_path)
@@ -213,33 +243,6 @@ def get_image(image, prompt, steps=50, cfg_scale=7.5, eta=1.0, fs=3, seed=123, i
 
 
     # @spaces.GPU
-def download_model():
-    REPO_ID = 'Doubiiu/ToonCrafter'
-    filename_list = ['model.ckpt']
-    if not os.path.exists('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/'):
-        os.makedirs('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/')
-    for filename in filename_list:
-        local_file = os.path.join('./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/', filename)
-        if not os.path.exists(local_file):
-            hf_hub_download(repo_id=REPO_ID, filename=filename, local_dir='./checkpoints/tooncrafter_'+str(resolution[1])+'_interp_v1/', local_dir_use_symlinks=False)
-    print("downloaded")
-    
-
-def get_latent_z_with_hidden_states(model, videos):
-    b, c, t, h, w = videos.shape
-    x = rearrange(videos, 'b c t h w -> (b t) c h w')
-    encoder_posterior, hidden_states = model.first_stage_model.encode(x, return_hidden_states=True)
-
-    hidden_states_first_last = []
-    ### use only the first and last hidden states
-    for hid in hidden_states:
-        hid = rearrange(hid, '(b t) c h w -> b c t h w', t=t)
-        hid_new = torch.cat([hid[:, :, 0:1], hid[:, :, -1:]], dim=2)
-        hidden_states_first_last.append(hid_new)
-
-    z = model.get_first_stage_encoding(encoder_posterior).detach()
-    z = rearrange(z, '(b t) c h w -> b c t h w', b=b, t=t)
-    return z, hidden_states_first_last