Add demo

gradio_app.py

@@ -0,0 +1,115 @@
+import logging
+import os
+import tempfile
+import time
+
+import gradio as gr
+import numpy as np
+import rembg
+import torch
+from PIL import Image
+
+from tsr.system import TSR
+from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation
+
+if torch.cuda.is_available():
+    device = "cuda:0"
+else:
+    device = "cpu"
+
+model = TSR.from_pretrained(
+    "stabilityai/TripoSR",
+    config_name="config.yaml",
+    weight_name="model.ckpt",
+)
+model.to(device)
+
+rembg_session = rembg.new_session()
+
+
+def check_input_image(input_image):
+    if input_image is None:
+        raise gr.Error("No image uploaded!")
+
+
+def preprocess(image_path, do_remove_background, foreground_ratio):
+    def fill_background(image):
+        image = np.array(image).astype(np.float32) / 255.0
+        image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5
+        image = Image.fromarray((image * 255.0).astype(np.uint8))
+        return image
+
+    if do_remove_background:
+        image = remove_background(Image.open(image_path), rembg_session)
+        image = resize_foreground(image, foreground_ratio)
+        image = fill_background(image)
+    else:
+        image = Image.open(image_path)
+        if image.mode == "RGBA":
+            image = fill_background(image)
+    return image
+
+
+def generate(image):
+    scene_codes = model(image, device=device)
+    mesh = model.extract_mesh(scene_codes)[0]
+    mesh.vertices = to_gradio_3d_orientation(mesh.vertices)
+    mesh_path = tempfile.NamedTemporaryFile(suffix=".obj", delete=False)
+    mesh.export(mesh_path.name)
+    return mesh_path.name
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    ## TripoSR Demo
+    [TripoSR](https://github.com/VAST-AI-Research/TripoSR) is a state-of-the-art open-source model for **fast** feedforward 3D reconstruction from a single image, collaboratively developed by [Tripo AI](https://www.tripo3d.ai/) and [Stability AI](https://stability.ai/).
+    """
+    )
+    with gr.Row(variant="panel"):
+        with gr.Column():
+            with gr.Row():
+                input_image = gr.Image(
+                    label="Input Image",
+                    sources="upload",
+                    type="filepath",
+                    elem_id="content_image",
+                )
+                processed_image = gr.Image(label="Processed Image", interactive=False)
+            with gr.Row():
+                with gr.Group():
+                    do_remove_background = gr.Checkbox(
+                        label="Remove Background", value=True
+                    )
+                    foreground_ratio = gr.Slider(
+                        label="Foreground Ratio",
+                        minimum=0.5,
+                        maximum=1.0,
+                        value=0.85,
+                        step=0.05,
+                    )
+            with gr.Row():
+                submit = gr.Button("Generate", elem_id="generate", variant="primary")
+        with gr.Column():
+            with gr.Tab("Model"):
+                output_model = gr.Model3D(
+                    label="Output Model",
+                    interactive=False,
+                )
+                gr.Markdown(
+                    """
+                Note: The model shown here will be flipped due to some visualization issues. Please download to get the correct result.
+                """
+                )
+    submit.click(fn=check_input_image, inputs=[input_image]).success(
+        fn=preprocess,
+        inputs=[input_image, do_remove_background, foreground_ratio],
+        outputs=[processed_image],
+    ).success(
+        fn=generate,
+        inputs=[processed_image],
+        outputs=[output_model],
+    )
+
+demo.queue(max_size=1)
+demo.launch()