Update app.py

app.py

@@ -1,8 +1,7 @@
 import gradio as gr
-from share_btn import community_icon_html, loading_icon_html, share_js
+
 import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
-from diffusers.utils import export_to_video
 
 pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16)
 pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
@@ -15,12 +14,21 @@ def create_image_caption(image_init):
     print("cap: " + cap)
     return cap
 
+def export_to_video(frames: np.ndarray, fps: int) -> str:
+    frames = np.clip((frames * 255), 0, 255).astype(np.uint8)
+    out_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
+    writer = imageio.get_writer(out_file.name, format="FFMPEG", fps=fps)
+    for frame in frames:
+        writer.append_data(frame)
+    writer.close()
+    return out_file.name
+
 def infer(image_init):
     prompt = create_image_caption(image_init)
-    video_frames = pipe(prompt, num_inference_steps=40, height=320, width=576, num_frames=24).frames
-    video_path = export_to_video(video_frames)
+    video_frames = pipe(prompt, num_inference_steps=40, height=320, width=576, num_frames=24).frames[0]
+    video_path = export_to_video(video_frames, 12)
     print(video_path)
-    return prompt, video_path, gr.Group.update(visible=True)
+    return prompt, video_path
 
 css = """
 #col-container {max-width: 510px; margin-left: auto; margin-right: auto;}
@@ -108,16 +116,9 @@ with gr.Blocks(css=css) as demo:
         coca_cap = gr.Textbox(label="Caption", placeholder="CoCa Caption will be displayed here", elem_id="coca-cap-in")
         video_result = gr.Video(label="Video Output", elem_id="video-output")
 
-        with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
-            community_icon = gr.HTML(community_icon_html)
-            loading_icon = gr.HTML(loading_icon_html)
-            share_button = gr.Button("Share to community", elem_id="share-btn")
-
     submit_btn.click(fn=infer,
                     inputs=[image_init],
-                    outputs=[coca_cap, video_result, share_group])
-    
-    share_button.click(None, [], [], _js=share_js)
+                    outputs=[coca_cap, video_result])
 
 demo.queue(max_size=12).launch()