update

.gitignore

@@ -0,0 +1,2 @@
+*.pyc
+*.pth

app.py

@@ -8,6 +8,7 @@ import ninja
 import torch
 from tqdm import trange
 import imageio
+import requests
 
 print('load!', flush=True)
 checkpoint = 'clevr.pth'
@@ -233,38 +234,39 @@ RT = torch.tensor([[ -1.0000,   0.0000,   0.0000,   0.0000,   0.0000,   0.5000,
 
 print('prepare finish', flush=True)
 
-def inference(name):
+def predict(name):
     print('inference', name, flush=True)
     gen = G(code, RT, bevs)
     rgb = gen['gen_output']['image'][0] * .5 + .5
     print('inference', name, flush=True)
-    return np.array(to_pil(rgb))
+    return to_pil(rgb)
 
     # to_pil(rgb).save('tmp.png')
     # save_path = '/mnt/petrelfs/zhangqihang/code/3d-scene-gen/tmp.png'
     # return [save_path]
 
+URL = "https://source.unsplash.com/random/500x500/?nature,fruit"
+
+def refresh(name):
+    image = Image.open(requests.get(URL, stream=True).raw)
+    return image
+
 with gr.Blocks() as demo:
     gr.HTML(
         """
-        abc
+        BerfScene demo
         """)
 
-    with gr.Group():
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    with gr.Column():
-                        with gr.Row():
-                            num_frames = gr.Dropdown(["24 - frames", "32 - frames", "40 - frames", "48 - frames", "56 - frames", "80 - recommended to run on local GPUs", "240 - recommended to run on local GPUs", "600 - recommended to run on local GPUs", "1200 - recommended to run on local GPUs", "10000 - recommended to run on local GPUs"], label="Number of Video Frames", info="For >56 frames use local workstation!", value="24 - frames")
+    # gallery = gr.Image(show_label=False)
+    image = gr.Image(show_label=False)
+    btn = gr.Button("Result")
 
-                with gr.Row():
-                    with gr.Row():
-                        btn = gr.Button("Result")
-        
-        gallery = gr.Image(label='img', show_label=True, elem_id="gallery")
+    x = gr.Textbox(label="Prompt", show_label=False, lines=1, max_lines=1, info="Describe your subject (optional)", value="a person", elem_id="prompt")
+    btn.click(fn=predict, inputs=x, outputs=image)
+    # demo.load(fn=refresh, inputs=x, outputs=gallery, show_progress=False, every=1)
 
-        btn.click(fn=inference, inputs=num_frames, outputs=[gallery], postprocess=False)
+        # btn.click(fn=predict, inputs=num_frames, outputs=gallery, postprocess=False)
 
 demo.queue()
-demo.launch(server_name='0.0.0.0', server_port=7860, debug=True, show_error=True)
+demo.launch(server_name='0.0.0.0', server_port=10093, debug=True, show_error=True)
+# demo.launch(server_name='0.0.0.0', server_port=7860, debug=True, show_error=True)