Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
|
@@ -34,6 +34,7 @@ import moviepy.editor as mp
|
|
| 34 |
import utils
|
| 35 |
from rife_model import load_rife_model, rife_inference_with_latents
|
| 36 |
from huggingface_hub import hf_hub_download, snapshot_download
|
|
|
|
| 37 |
|
| 38 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
| 39 |
|
|
@@ -240,6 +241,9 @@ def infer(
|
|
| 240 |
guidance_scale=guidance_scale,
|
| 241 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 242 |
).frames
|
|
|
|
|
|
|
|
|
|
| 243 |
elif image_input is not None:
|
| 244 |
pipe_image.to(device)
|
| 245 |
image_input = Image.fromarray(image_input).resize(size=(720, 480)) # Convert to PIL
|
|
@@ -255,6 +259,7 @@ def infer(
|
|
| 255 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 256 |
).frames
|
| 257 |
pipe_image.to("cpu")
|
|
|
|
| 258 |
else:
|
| 259 |
pipe.to(device)
|
| 260 |
video_pt = pipe(
|
|
@@ -268,6 +273,7 @@ def infer(
|
|
| 268 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 269 |
).frames
|
| 270 |
pipe.to("cpu")
|
|
|
|
| 271 |
return (video_pt, seed)
|
| 272 |
|
| 273 |
|
|
|
|
| 34 |
import utils
|
| 35 |
from rife_model import load_rife_model, rife_inference_with_latents
|
| 36 |
from huggingface_hub import hf_hub_download, snapshot_download
|
| 37 |
+
import gc
|
| 38 |
|
| 39 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
| 40 |
|
|
|
|
| 241 |
guidance_scale=guidance_scale,
|
| 242 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 243 |
).frames
|
| 244 |
+
del pipe_video
|
| 245 |
+
gc.collect()
|
| 246 |
+
torch.cuda.empty_cache()
|
| 247 |
elif image_input is not None:
|
| 248 |
pipe_image.to(device)
|
| 249 |
image_input = Image.fromarray(image_input).resize(size=(720, 480)) # Convert to PIL
|
|
|
|
| 259 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 260 |
).frames
|
| 261 |
pipe_image.to("cpu")
|
| 262 |
+
gc.collect()
|
| 263 |
else:
|
| 264 |
pipe.to(device)
|
| 265 |
video_pt = pipe(
|
|
|
|
| 273 |
generator=torch.Generator(device="cpu").manual_seed(seed),
|
| 274 |
).frames
|
| 275 |
pipe.to("cpu")
|
| 276 |
+
gc.collect()
|
| 277 |
return (video_pt, seed)
|
| 278 |
|
| 279 |
|