Files changed (1) hide show
  1. app.py +21 -11
app.py CHANGED
@@ -10,7 +10,7 @@ from pathlib import Path
10
  from typing import Optional
11
 
12
  from diffusers import StableVideoDiffusionPipeline
13
- from diffusers.utils import export_to_video
14
  from PIL import Image
15
 
16
  fps25Pipe = StableVideoDiffusionPipeline.from_pretrained(
@@ -63,9 +63,18 @@ def animate(
63
 
64
  os.makedirs(output_folder, exist_ok=True)
65
  base_count = len(glob(os.path.join(output_folder, "*." + video_format)))
66
- video_path = os.path.join(output_folder, f"{base_count:06d}." + video_format)
67
 
68
- export_to_video(frames, video_path, fps=fps_id)
 
 
 
 
 
 
 
 
 
69
  end = time.time()
70
  secondes = int(end - start)
71
  minutes = math.floor(secondes / 60)
@@ -79,7 +88,7 @@ def animate(
79
  ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + \
80
  str(secondes) + " sec."
81
 
82
- return gr.update(value=video_path, format=video_format), gr.update(value=video_path, visible=True), gr.update(label="Generated frames in *." + frame_format + " format", format = frame_format, value = frames, visible=True), seed, gr.update(value = information, visible = True), gr.update(visible=True)
83
 
84
  @spaces.GPU(duration=120)
85
  def animate_on_gpu(
@@ -131,8 +140,7 @@ def resize_image(image, output_size=(1024, 576)):
131
  bottom = (new_height + output_size[1]) / 2
132
 
133
  # Crop the image
134
- cropped_image = resized_image.crop((left, top, right, bottom))
135
- return cropped_image
136
 
137
  def reset():
138
  return [
@@ -167,7 +175,7 @@ with gr.Blocks() as demo:
167
  motion_bucket_id = gr.Slider(label="Motion bucket id", info="Controls how much motion to add/remove from the image", value=127, minimum=1, maximum=255)
168
  noise_aug_strength = gr.Slider(label="Noise strength", info="The noise to add", value=0.1, minimum=0, maximum=1, step=0.1)
169
  decoding_t = gr.Slider(label="Decoding", info="Number of frames decoded at a time; this eats more VRAM; reduce if necessary", value=3, minimum=1, maximum=5, step=1)
170
- video_format = gr.Radio([["*.mp4", "mp4"]], label="Video format for result", info="File extention", value="mp4", interactive=True)
171
  frame_format = gr.Radio([["*.webp", "webp"], ["*.png", "png"], ["*.jpeg", "jpeg"], ["*.gif (unanimated)", "gif"], ["*.bmp", "bmp"]], label="Image format for frames", info="File extention", value="webp", interactive=True)
172
  version = gr.Radio([["Auto", "auto"], ["πŸƒπŸ»β€β™€οΈ SVD (trained on 14 f/s)", "svd"], ["πŸƒπŸ»β€β™€οΈπŸ’¨ SVD-XT (trained on 25 f/s)", "svdxt"]], label="Model", info="Trained model", value="auto", interactive=True)
173
  seed = gr.Slider(label="Seed", value=42, randomize=True, minimum=0, maximum=max_64_bit_int, step=1)
@@ -177,9 +185,10 @@ with gr.Blocks() as demo:
177
  reset_btn = gr.Button(value="🧹 Reinit page", variant="stop", elem_id="reset_button", visible = False)
178
 
179
  with gr.Column():
180
- video = gr.Video(label="Generated video", autoplay=True)
 
181
  download_button = gr.DownloadButton(label="πŸ’Ύ Download video", visible=False)
182
- information_msg = gr.HTML(visible = False)
183
  gallery = gr.Gallery(label="Generated frames", visible=False)
184
 
185
  image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
@@ -195,7 +204,8 @@ with gr.Blocks() as demo:
195
  frame_format,
196
  version
197
  ], outputs=[
198
- video,
 
199
  download_button,
200
  gallery,
201
  seed,
@@ -223,7 +233,7 @@ with gr.Blocks() as demo:
223
  ["Examples/Town.jpeg", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto"]
224
  ],
225
  inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id, noise_aug_strength, decoding_t, video_format, frame_format, version],
226
- outputs=[video, download_button, gallery, seed, information_msg, reset_btn],
227
  fn=animate,
228
  run_on_click=True,
229
  cache_examples=False,
 
10
  from typing import Optional
11
 
12
  from diffusers import StableVideoDiffusionPipeline
13
+ from diffusers.utils import export_to_video, export_to_gif
14
  from PIL import Image
15
 
16
  fps25Pipe = StableVideoDiffusionPipeline.from_pretrained(
 
63
 
64
  os.makedirs(output_folder, exist_ok=True)
65
  base_count = len(glob(os.path.join(output_folder, "*." + video_format)))
66
+ result_path = os.path.join(output_folder, f"{base_count:06d}." + video_format)
67
 
68
+ if video_format == "gif":
69
+ video_path = None
70
+ gif_path = result_path
71
+ video_format = None
72
+ export_to_gif(image=frames, output_gif_path=gif_path, fps=fps_id)
73
+ else:
74
+ video_path = result_path
75
+ gif_path = None
76
+ export_to_video(frames, video_path, fps=fps_id)
77
+
78
  end = time.time()
79
  secondes = int(end - start)
80
  minutes = math.floor(secondes / 60)
 
88
  ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + \
89
  str(secondes) + " sec."
90
 
91
+ return gr.update(value=video_path, format=video_format), gr.update(value=gif_path, visible=video_format == "gif"), gr.update(value=result_path, visible=True), gr.update(label="Generated frames in *." + frame_format + " format", format = frame_format, value = frames, visible=True), seed, gr.update(value = information, visible = True), gr.update(visible=True)
92
 
93
  @spaces.GPU(duration=120)
94
  def animate_on_gpu(
 
140
  bottom = (new_height + output_size[1]) / 2
141
 
142
  # Crop the image
143
+ return resized_image.crop((left, top, right, bottom))
 
144
 
145
  def reset():
146
  return [
 
175
  motion_bucket_id = gr.Slider(label="Motion bucket id", info="Controls how much motion to add/remove from the image", value=127, minimum=1, maximum=255)
176
  noise_aug_strength = gr.Slider(label="Noise strength", info="The noise to add", value=0.1, minimum=0, maximum=1, step=0.1)
177
  decoding_t = gr.Slider(label="Decoding", info="Number of frames decoded at a time; this eats more VRAM; reduce if necessary", value=3, minimum=1, maximum=5, step=1)
178
+ video_format = gr.Radio([["*.mp4", "mp4"], ["*.gif", "gif"]], label="Video format for result", info="File extention", value="mp4", interactive=True)
179
  frame_format = gr.Radio([["*.webp", "webp"], ["*.png", "png"], ["*.jpeg", "jpeg"], ["*.gif (unanimated)", "gif"], ["*.bmp", "bmp"]], label="Image format for frames", info="File extention", value="webp", interactive=True)
180
  version = gr.Radio([["Auto", "auto"], ["πŸƒπŸ»β€β™€οΈ SVD (trained on 14 f/s)", "svd"], ["πŸƒπŸ»β€β™€οΈπŸ’¨ SVD-XT (trained on 25 f/s)", "svdxt"]], label="Model", info="Trained model", value="auto", interactive=True)
181
  seed = gr.Slider(label="Seed", value=42, randomize=True, minimum=0, maximum=max_64_bit_int, step=1)
 
185
  reset_btn = gr.Button(value="🧹 Reinit page", variant="stop", elem_id="reset_button", visible = False)
186
 
187
  with gr.Column():
188
+ video_output = gr.Video(label="Generated video", autoplay=True)
189
+ gif_output = gr.Image(label="Generated video", format="gif", visible=False)
190
  download_button = gr.DownloadButton(label="πŸ’Ύ Download video", visible=False)
191
+ information_msg = gr.HTML(visible=False)
192
  gallery = gr.Gallery(label="Generated frames", visible=False)
193
 
194
  image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
 
204
  frame_format,
205
  version
206
  ], outputs=[
207
+ video_output,
208
+ gif_output,
209
  download_button,
210
  gallery,
211
  seed,
 
233
  ["Examples/Town.jpeg", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto"]
234
  ],
235
  inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id, noise_aug_strength, decoding_t, video_format, frame_format, version],
236
+ outputs=[video_output, gif_output, download_button, gallery, seed, information_msg, reset_btn],
237
  fn=animate,
238
  run_on_click=True,
239
  cache_examples=False,