Upload app.py

app.py

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+import gradio as gr
+import numpy as np
+import spaces
+import torch
+import rembg
+from PIL import Image
+from functools import partial
+
+import logging
+import os
+import shlex
+import subprocess
+import tempfile
+import time
+
+subprocess.run(shlex.split('pip install wheel/torchmcubes-0.1.0-cp310-cp310-linux_x86_64.whl'))
+
+from tsr.system import TSR
+from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation
+
+
+STEP1_HEADER = """
+# Step 1: Generate the 3D Mesh
+
+For this step, we use TripoSR, an open-source model for **fast** feedforward 3D reconstruction from a single image, developed in collaboration between [Tripo AI](https://www.tripo3d.ai/) and [Stability AI](https://stability.ai/).
+
+During this step, you need to upload an image of what you want to generate a 3D Model from.
+
+
+## 💡 Tips
+
+-  If there's a background, ✅ Remove background.
+
+- If you find the result is unsatisfied, please try to change the foreground ratio. It might improve the results.
+
+
+"""
+
+# These part of the code (check_input_image and preprocess were taken from https://huggingface.co/spaces/stabilityai/TripoSR/blob/main/app.py)
+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.renderer.set_chunk_size(131072)
+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(input_image, 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 = input_image.convert("RGB")
+        image = remove_background(image, rembg_session)
+        image = resize_foreground(image, foreground_ratio)
+        image = fill_background(image)
+    else:
+        image = input_image
+        if image.mode == "RGBA":
+            image = fill_background(image)
+    return image
+
+
+@spaces.GPU
+def generate(image, mc_resolution, formats=["obj", "glb"]):
+    scene_codes = model(image, device=device)
+    mesh = model.extract_mesh(scene_codes, resolution=mc_resolution)[0]
+    mesh = to_gradio_3d_orientation(mesh)
+
+    mesh_path_glb = tempfile.NamedTemporaryFile(suffix=f".glb", delete=False)
+    mesh.export(mesh_path_glb.name)
+
+    mesh_path_obj = tempfile.NamedTemporaryFile(suffix=f".obj", delete=False)
+    mesh.apply_scale([-1, 1, 1])  # Otherwise the visualized .obj will be flipped
+    mesh.export(mesh_path_obj.name)
+    
+    return mesh_path_obj.name, mesh_path_glb.name
+
+
+with gr.Blocks() as demo:
+	gr.Markdown(STEP1_HEADER)
+	with gr.Row(variant = "panel"):
+		with gr.Column():
+			with gr.Row():
+				input_image = gr.Image(
+					label = "Input Image",
+					image_mode = "RGBA",
+					sources = "upload",
+					type="pil",
+					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,
+						)
+					mc_resolution = gr.Slider(
+						label="Marching Cubes Resolution",
+						minimum=32,
+						maximum=320,
+						value=256,
+						step=32
+						)
+			with gr.Row():
+				step1_submit = gr.Button("Generate", elem_id="generate", variant="primary")
+
+		with gr.Column():
+			with gr.Tab("OBJ"):
+				output_model_obj = gr.Model3D(
+					label = "Output Model (OBJ Format)",
+					interative = False,
+				)
+				gr.Markdown("Note: Downloaded object will be flipped in case of .obj export. Export .glb instead or manually flip it before usage.")
+            with gr.Tab("GLB"):
+                output_model_glb = gr.Model3D(
+                    label="Output Model (GLB Format)",
+                    interactive=False,
+                )
+                gr.Markdown("Note: The model shown here has a darker appearance. Download to get correct results.")
+
+	step1_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, mc_resolution],
+        outputs=[output_model_obj, output_model_glb],
+    )
+
+demo.queue(max_size=10)
+demo.launch()