add app

app.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import os
+
+from torch import is_inference
+from pq3d.inference import inference
+
+MESH_DIR = 'assets/mesh'
+MESH_NAMES = sorted([os.path.splitext(fname)[0] for fname in os.listdir(MESH_DIR)])
+
+def change_scene(dropdown_scene: str):
+    # reset 3D scene and chatbot history
+    return os.path.join(MESH_DIR, f'{dropdown_scene}.glb')
+
+with gr.Blocks(title='PQ3D Demo') as demo:
+    gr.HTML(value="<h1 align='center'>Unifying 3D Vision Language Understanding vis Promptable Queries </h1>")
+    #gr.HTML(value="<div align='center' style='margin-top:-1em; margin-bottom:-1em;'><img src='/file=assets/leo.svg' width='4%'></div>")
+    # gr.HTML(value="<img src='/file=assets/teaser.png' alt='Teaser' width='760px' style='display: block; margin: auto;'>")
+    #gr.HTML(value="<p align='center' style='font-size: 1.2em; color: #485fc7;'><a href='https://arxiv.org/abs/2311.12871' target='_blank'>arXiv</a> | <a href='https://embodied-generalist.github.io/' target='_blank'>Project Page</a> | <a href='https://github.com/embodied-generalist/embodied-generalist' target='_blank'>Code</a></p>")
+    #gr.HTML(value="<p align='center' style='font-size: 1.15em;'><i>LEO: an embodied generalist agent capable of perceiving, grounding, reasoning, planning, and acting in 3D world.</i></p>")
+
+    with gr.Row():
+        with gr.Column(scale=5):
+            dropdown_scene = gr.Dropdown(
+                choices=MESH_NAMES,
+                value='scene0050_00',
+                interactive=True,
+                label='Select a 3D scene',
+            )
+            model_3d = gr.Model3D(
+                value=os.path.join(MESH_DIR, f'scene0050_00.glb'),
+                clear_color=[0.0, 0.0, 0.0, 0.0],
+                label='3D Scene',
+                camera_position=(80, 100, 6),
+                height=659,
+            )
+            gr.HTML(
+                """<center><strong>
+                👆 SCROLL and DRAG on the 3D Scene
+                to zoom in/out and rotate. Press CTRL and DRAG to pan.
+                </strong></center>
+                """
+            )
+    
+    dropdown_scene.change(
+        fn=change_scene,
+        inputs=[dropdown_scene],
+        outputs=[model_3d],
+        queue=False
+    )
+    
+    def inference_wrapper(text):
+        scan_id = model_3d.value['orig_name'].split('.')[0]
+        inst_id = inference(scan_id, text)
+        return f"assets/mask/{scan_id}/{scan_id}_obj_{inst_id}.glb"
+    
+    gr.Interface(
+        fn=inference_wrapper,
+        inputs=["text"],
+        outputs=gr.Model3D(
+                clear_color=[0.0, 0.0, 0.0, 0.0],  camera_position=(80, 100, 6), label="3D Model"),
+        examples=[
+            ["armchair"], ["Sofa"], ["left computer on the desk"]
+        ],
+        title="Input text, Output 3D Mask,  Red denotes predicted object"
+    )
+
+demo.queue().launch(share=True, allowed_paths=['assets'])