| import logging |
| import os |
| import shlex |
| import subprocess |
| import tempfile |
| import time |
|
|
| import gradio as gr |
| import numpy as np |
| import rembg |
| import spaces |
| import torch |
| from PIL import Image |
| from functools import partial |
|
|
| subprocess.run( |
| shlex.split("pip install --no-build-isolation git+https://github.com/tatsy/torchmcubes.git"), |
| env={**os.environ, "TORCH_CUDA_ARCH_LIST": "12.0+PTX"}, |
| check=True, |
| ) |
|
|
| from tsr.system import TSR |
| from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation |
|
|
|
|
| HEADER = """ |
| # TripoSR Demo |
| <table bgcolor="#1E2432" cellspacing="0" cellpadding="0" width="450"> |
| <tr style="height:50px;"> |
| <td style="text-align: center;"> |
| <a href="https://stability.ai"> |
| <img src="https://images.squarespace-cdn.com/content/v1/6213c340453c3f502425776e/6c9c4c25-5410-4547-bc26-dc621cdacb25/Stability+AI+logo.png" width="200" height="40" /> |
| </a> |
| </td> |
| <td style="text-align: center;"> |
| <a href="https://www.tripo3d.ai"> |
| <img src="https://tripo-public.cdn.bcebos.com/logo.png" width="40" height="40" /> |
| </a> |
| </td> |
| </tr> |
| </table> |
| <table bgcolor="#1E2432" cellspacing="0" cellpadding="0" width="450"> |
| <tr style="height:30px;"> |
| <td style="text-align: center;"> |
| <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> |
| </td> |
| <td style="text-align: center;"> |
| <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> |
| </td> |
| <td style="text-align: center; color: white;"> |
| <a href="https://arxiv.org/abs/2403.02151"><img src="https://img.shields.io/badge/arXiv-2403.02151-b31b1b.svg" height="20"></a> |
| </td> |
| </tr> |
| </table> |
| |
| > Try our new model: **SF3D** with several improvements such as faster generation and more game-ready assets. |
| > |
| > The model is available [here](https://huggingface.co/stabilityai/stable-fast-3d) and we also have a [demo](https://huggingface.co/spaces/stabilityai/stable-fast-3d). |
| |
| |
| **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/). |
| |
| **Tips:** |
| 1. If you find the result is unsatisfied, please try to change the foreground ratio. It might improve the results. |
| 2. It's better to disable "Remove Background" for the provided examples since they have been already preprocessed. |
| 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. |
| """ |
|
|
|
|
| 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]) |
| mesh.export(mesh_path_obj.name) |
| |
| return mesh_path_obj.name, mesh_path_glb.name |
|
|
| def run_example(image_pil): |
| preprocessed = preprocess(image_pil, False, 0.9) |
| mesh_name_obj, mesh_name_glb = generate(preprocessed, 256, ["obj", "glb"]) |
| return preprocessed, mesh_name_obj, mesh_name_glb |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown(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(): |
| 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)", |
| interactive=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.") |
| with gr.Row(variant="panel"): |
| gr.Examples( |
| examples=[ |
| os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples")) |
| ], |
| inputs=[input_image], |
| outputs=[processed_image, output_model_obj, output_model_glb], |
| cache_examples=True, |
| fn=partial(run_example), |
| label="Examples", |
| examples_per_page=20 |
| ) |
| 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() |
|
|