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import logging |
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import os |
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import shlex |
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import subprocess |
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import tempfile |
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import time |
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import gradio as gr |
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import numpy as np |
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import rembg |
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import spaces |
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import torch |
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from PIL import Image |
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from functools import partial |
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subprocess.run(shlex.split('pip install wheel/torchmcubes-0.1.0-cp310-cp310-linux_x86_64.whl')) |
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from tsr.system import TSR |
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from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation |
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HEADER = """ |
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# TripoSR Demo |
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<table bgcolor="#1E2432" cellspacing="0" cellpadding="0" width="450"> |
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<tr style="height:50px;"> |
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<td style="text-align: center;"> |
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<a href="https://stability.ai"> |
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<img src="https://images.squarespace-cdn.com/content/v1/6213c340453c3f502425776e/6c9c4c25-5410-4547-bc26-dc621cdacb25/Stability+AI+logo.png" width="200" height="40" /> |
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</a> |
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</td> |
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<td style="text-align: center;"> |
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<a href="https://www.tripo3d.ai"> |
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<img src="https://tripo-public.cdn.bcebos.com/logo.png" width="40" height="40" /> |
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</a> |
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</td> |
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</tr> |
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</table> |
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<table bgcolor="#1E2432" cellspacing="0" cellpadding="0" width="450"> |
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<tr style="height:30px;"> |
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<td style="text-align: center;"> |
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<a href="https://huggingface.co/stabilityai/TripoSR"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Model_Card-Huggingface-orange" height="20"></a> |
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</td> |
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<td style="text-align: center;"> |
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<a href="https://github.com/VAST-AI-Research/TripoSR"><img src="https://postimage.me/images/2024/03/04/GitHub_Logo_White.png" width="100" height="20"></a> |
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</td> |
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<td style="text-align: center; color: white;"> |
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<a href="https://arxiv.org/abs/2403.02151"><img src="https://img.shields.io/badge/arXiv-2403.02151-b31b1b.svg" height="20"></a> |
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</td> |
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</tr> |
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</table> |
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**TripoSR** is a state-of-the-art 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/). |
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**Tips:** |
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1. If you find the result is unsatisfied, please try to change the foreground ratio. It might improve the results. |
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2. It's better to disable "Remove Background" for the provided examples since they have been already preprocessed. |
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3. Otherwise, please disable "Remove Background" option only if your input image is RGBA with transparent background, image contents are centered and occupy more than 70% of image width or height. |
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""" |
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if torch.cuda.is_available(): |
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device = "cuda:0" |
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else: |
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device = "cpu" |
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model = TSR.from_pretrained( |
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"stabilityai/TripoSR", |
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config_name="config.yaml", |
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weight_name="model.ckpt", |
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) |
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model.renderer.set_chunk_size(131072) |
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model.to(device) |
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rembg_session = rembg.new_session() |
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def check_input_image(input_image): |
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if input_image is None: |
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raise gr.Error("No image uploaded!") |
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def preprocess(input_image, do_remove_background, foreground_ratio): |
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def fill_background(image): |
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image = np.array(image).astype(np.float32) / 255.0 |
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image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5 |
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image = Image.fromarray((image * 255.0).astype(np.uint8)) |
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return image |
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if do_remove_background: |
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image = input_image.convert("RGB") |
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image = remove_background(image, rembg_session) |
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image = resize_foreground(image, foreground_ratio) |
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image = fill_background(image) |
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else: |
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image = input_image |
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if image.mode == "RGBA": |
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image = fill_background(image) |
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return image |
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@spaces.GPU |
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def generate(image, mc_resolution, formats=["obj", "glb"]): |
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scene_codes = model(image, device=device) |
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mesh = model.extract_mesh(scene_codes, resolution=mc_resolution)[0] |
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mesh = to_gradio_3d_orientation(mesh) |
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mesh_path_glb = tempfile.NamedTemporaryFile(suffix=f".glb", delete=False) |
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mesh.export(mesh_path_glb.name) |
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mesh_path_obj = tempfile.NamedTemporaryFile(suffix=f".obj", delete=False) |
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mesh.apply_scale([-1, 1, 1]) |
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mesh.export(mesh_path_obj.name) |
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return mesh_path_obj.name, mesh_path_glb.name |
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def run_example(image_pil): |
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preprocessed = preprocess(image_pil, False, 0.9) |
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mesh_name_obj, mesh_name_glb = generate(preprocessed, 256, ["obj", "glb"]) |
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return preprocessed, mesh_name_obj, mesh_name_glb |
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with gr.Blocks() as demo: |
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gr.Markdown(HEADER) |
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with gr.Row(variant="panel"): |
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with gr.Column(): |
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with gr.Row(): |
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input_image = gr.Image( |
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label="Input Image", |
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image_mode="RGBA", |
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sources="upload", |
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type="pil", |
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elem_id="content_image", |
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) |
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processed_image = gr.Image(label="Processed Image", interactive=False) |
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with gr.Row(): |
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with gr.Group(): |
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do_remove_background = gr.Checkbox( |
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label="Remove Background", value=True |
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) |
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foreground_ratio = gr.Slider( |
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label="Foreground Ratio", |
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minimum=0.5, |
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maximum=1.0, |
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value=0.85, |
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step=0.05, |
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) |
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mc_resolution = gr.Slider( |
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label="Marching Cubes Resolution", |
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minimum=32, |
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maximum=320, |
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value=256, |
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step=32 |
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) |
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with gr.Row(): |
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submit = gr.Button("Generate", elem_id="generate", variant="primary") |
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with gr.Column(): |
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with gr.Tab("OBJ"): |
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output_model_obj = gr.Model3D( |
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label="Output Model (OBJ Format)", |
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interactive=False, |
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) |
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gr.Markdown("Note: Downloaded object will be flipped in case of .obj export. Export .glb instead or manually flip it before usage.") |
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with gr.Tab("GLB"): |
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output_model_glb = gr.Model3D( |
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label="Output Model (GLB Format)", |
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interactive=False, |
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) |
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gr.Markdown("Note: The model shown here has a darker appearance. Download to get correct results.") |
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with gr.Row(variant="panel"): |
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gr.Examples( |
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examples=[ |
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os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples")) |
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], |
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inputs=[input_image], |
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outputs=[processed_image, output_model_obj, output_model_glb], |
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cache_examples=True, |
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fn=partial(run_example), |
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label="Examples", |
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examples_per_page=20 |
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) |
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submit.click(fn=check_input_image, inputs=[input_image]).success( |
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fn=preprocess, |
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inputs=[input_image, do_remove_background, foreground_ratio], |
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outputs=[processed_image], |
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).success( |
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fn=generate, |
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inputs=[processed_image, mc_resolution], |
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outputs=[output_model_obj, output_model_glb], |
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) |
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demo.queue(max_size=10) |
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demo.launch() |
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