return local output url

app.py

@@ -22,7 +22,7 @@ with gr.Blocks() as demo:
             submit_btn = gr.Button(value="Generate")
         with gr.Column():
             animation = gr.Video(label="Result")
-            frames = gr.Gallery(type="filepath", label="Frames", format="png")
+            frames = gr.Gallery(type="pil", label="Frames", format="png")
 
     submit_btn.click(
         run_app, inputs=[char_imgs, mocap, tr_steps, inf_steps, fps, remove_bg, resize_inputs], outputs=[animation, frames]

main.py

@@ -60,7 +60,7 @@ from numba import cuda
 import requests
 import uuid
 
-from huggingface_hub import hf_hub_download
+from huggingface_hub import hf_hub_download, HfApi
 
 
 # Inputs ===================================================================================================
@@ -86,11 +86,16 @@ def save_temp_imgs(imgs):
     os.makedirs('temp', exist_ok=True)
     results = []
 
-    for img in imgs:
+    api = HfApi()
+    
+
+    for i, img in enumerate(imgs):
 
-        img_name = 'temp/'+str(uuid.uuid4())+'.png'
+        #img_name = 'temp/'+str(uuid.uuid4())+'.png'
+        img_name = 'temp/'+str(i)+'.png'
         img.save(img_name)
 
+        """
         url = 'https://tmpfiles.org/api/v1/upload'
 
         try:
@@ -108,6 +113,16 @@ def save_temp_imgs(imgs):
 
         except requests.exceptions.RequestException as e:
             print(f"An error occurred: {e}")
+        """
+
+        results.append('https://huggingface.co/datasets/acmyu/KeyframesAIFiles/resolve/main/'+img_name)
+
+    api.upload_file(
+        path_or_fileobj='temp',
+        path_in_repo='temp',
+        repo_id="acmyu/KeyframesAIFiles",
+        repo_type="dataset",
+    )
 
     return results
 
@@ -1088,7 +1103,7 @@ def run_inference(images, video_path, train_steps=100, inference_steps=10, fps=1
     target_poses, in_pose = prepare_inputs_inference(in_img, video_path, fps, dwpose, 'target', is_app)
     
     results = inference(modelId, in_img, in_pose, target_poses, inference_steps, None, vae, unet, image_encoder_p, is_app)
-    urls = save_temp_imgs(results)
+    #urls = save_temp_imgs(results)
 
     if should_gen_vid:
         if debug:
@@ -1098,7 +1113,7 @@ def run_inference(images, video_path, train_steps=100, inference_steps=10, fps=1
     
     print("Done!")
     
-    return out_vid+'.webm', urls
+    return out_vid+'.webm', results
     
 
 def run_app(images, video_path, train_steps=100, inference_steps=10, fps=12, bg_remove=False, resize_inputs=True):