Update app.py

app.py

@@ -99,7 +99,9 @@ def predict(_chatbot,task_history,viewer_voxel,viewer_mesh,task_new,seed,top_k,t
             if is_video_file(q[0]):
                 content.append({'video': f'file://{q[0]}'})
             else:
-                content.append({'image': f'file://{q[0]}'})
+                pipeline_image.preprocess_image_white(Image.open(q[0])).save(f"{TMP_DIR}/{trial_id}.png", "png")
+                content.append({'image': f'file://{TMP_DIR}/{trial_id}.png'})
+                #content.append({'image': f'file://{q[0]}'})
         else:
             content.append({'text': q})
             messages.append({'role': 'user', 'content': content})
@@ -284,18 +286,18 @@ def add_text(history, task_history, text,task_new):
 def add_file(history, task_history, file, task_new, fig, query):
     if file.name.endswith(('.obj', '.glb')):
         position_recon = load_vertices(file.name)#(N,3)
-        coords        = ((torch.from_numpy(position_recon) + 0.5) * 64).int().contiguous()
-        ss            = torch.zeros(1, 64, 64, 64, dtype=torch.long)
+        coords         = ((torch.from_numpy(position_recon) + 0.5) * 64).int().contiguous()
+        ss             = torch.zeros(1, 64, 64, 64, dtype=torch.long)
         ss[:, coords[:, 0], coords[:, 1], coords[:, 2]] = 1
-        token         = vqvae.Encode(ss.to(dtype=torch.float32).unsqueeze(0).to("cuda"))
-        token         = token[0].cpu().numpy().tolist()
-        words         = token_to_words(token)
-        fig           = make_pointcloud_figure(position_recon,rotate=True)
+        token          = vqvae.Encode(ss.to(dtype=torch.float32).unsqueeze(0).to("cuda"))
+        token          = token[0].cpu().numpy().tolist()
+        words          = token_to_words(token)
+        fig            = make_pointcloud_figure(position_recon,rotate=True)
         return history, task_history,file.name,task_new,fig,gr.update(
-            value=f"{words}\nGive a quick overview of the object represented by this 3D mesh.")
-    history = history if history is not None else []
+            value= f"{words}\nGive a quick overview of the object represented by this 3D mesh.")
+    history      = history if history is not None else []
     task_history = task_history if task_history is not None else []
-    history = history + [((file.name,), None)]
+    history      = history + [((file.name,), None)]
     task_history = task_history + [((file.name,), None)]
     task_new     = task_new + [((file.name,), None)]
     return history, task_history, file.name, task_new, fig, query
@@ -404,7 +406,7 @@ def add_file2(history, task_history, file,task_new):
     history = history + [((file,), None)]
     task_history = task_history + [((file,), None)]
     task_new     = task_new + [((file,), None)]
-    return history, task_history,file,task_new
+    return history, task_history, file, task_new
 
 def _transform_messages(original_messages):
     transformed_messages = []