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import logging |
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import os |
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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 torch |
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from PIL import Image |
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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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HF_TOKEN = os.getenv("HF_TOKEN") |
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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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token=HF_TOKEN |
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) |
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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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def generate(image): |
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scene_codes = model(image, device=device) |
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mesh = model.extract_mesh(scene_codes)[0] |
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mesh.vertices = to_gradio_3d_orientation(mesh.vertices) |
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mesh_path = tempfile.NamedTemporaryFile(suffix=".obj", delete=False) |
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mesh.export(mesh_path.name) |
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return mesh_path.name |
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with gr.Blocks() as demo: |
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gr.Markdown( |
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""" |
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## TripoSR Demo |
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[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/). |
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""" |
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) |
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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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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("Model"): |
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output_model = gr.Model3D( |
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label="Output Model", |
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interactive=False, |
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) |
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gr.Markdown( |
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""" |
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Note: The model shown here will be flipped due to some visualization issues. Please download to get the correct result. |
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""" |
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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], |
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outputs=[output_model], |
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) |
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demo.queue(max_size=10) |
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demo.launch() |
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