Update app.py

app.py

@@ -11,7 +11,7 @@ from moviepy import VideoFileClip
 from datetime import datetime, timedelta
 from huggingface_hub import hf_hub_download, snapshot_download, login
 HF_TOKEN=os.environ.get('HF_TOKEN')
-login(token=HF_TOKEN)
+##login(token=HF_TOKEN)
 import insightface
 from insightface.app import FaceAnalysis
 from facexlib.parsing import init_parsing_model
@@ -41,7 +41,7 @@ snapshot_download(repo_id="BestWishYsh/ConsisID-preview", local_dir="BestWishYsh
 model_path = "BestWishYsh/ConsisID-preview"
 lora_path = None
 lora_rank = 128
-dtype = torch.float16
+dtype = torch.bfloat16
 
 if os.path.exists(os.path.join(model_path, "transformer_ema")):
     subfolder = "transformer_ema"
@@ -139,15 +139,8 @@ def delete_old_files():
                     if file_mtime < cutoff:
                         os.remove(file_path)
         time.sleep(600)
-
-def infer(
-    prompt: str,
-    image_input: str,
-    num_inference_steps: int,
-    guidance_scale: float,
-    seed: int = 42,
-    progress=gr.Progress(track_tqdm=True),
-):
+@spaces.GPU(duration=70)
+def infer(prompt,image_input,seed_value,scale_status,rife_status,progress=gr.Progress(track_tqdm=True)):
     if seed == -1:
         seed = random.randint(0, 2**8 - 1)
 
@@ -178,24 +171,19 @@ def infer(
         prompt=prompt,
         image=image,
         num_videos_per_prompt=1,
-        num_inference_steps=num_inference_steps,
+        num_inference_steps=4,
         num_frames=49,
         use_dynamic_cfg=False,
-        guidance_scale=guidance_scale,
+        guidance_scale=7.0,
         generator=generator,
         id_vit_hidden=id_vit_hidden,
         id_cond=id_cond,
         kps_cond=kps_cond,
         output_type="pt",
     ).frames
-    
-    ##free_memory()
-    return video_pt, seed
-##threading.Thread(target=delete_old_files, daemon=True).start()
-@spaces.GPU(duration=70)
-def generate(prompt,image_input,seed_value,scale_status,rife_status,progress=gr.Progress(track_tqdm=True)):
 
-    latents, seed = infer(prompt,image_input,num_inference_steps=4,guidance_scale=7.0,seed=seed_value,progress=progress,)
+    latents = video_pt
+    ##free_memory()
     if scale_status:
         latents = upscale_batch_and_concatenate(upscale_model, latents, device)
     if rife_status:
@@ -219,6 +207,8 @@ def generate(prompt,image_input,seed_value,scale_status,rife_status,progress=gr.
 
     return video_path, video_update, gif_update, seed_update
 
+    ##return video_pt, seed
+##threading.Thread(target=delete_old_files, daemon=True).start()
 
 examples_images = [
     ["asserts/example_images/1.png", "A woman adorned with a delicate flower crown, is standing amidst a field of gently swaying wildflowers. Her eyes sparkle with a serene gaze, and a faint smile graces her lips, suggesting a moment of peaceful contentment. The shot is framed from the waist up, highlighting the gentle breeze lightly tousling her hair. The background reveals an expansive meadow under a bright blue sky, capturing the tranquility of a sunny afternoon."],