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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 functools import partial | |
from tsr.system import TSR | |
from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation | |
#HF_TOKEN = os.getenv("HF_TOKEN") | |
HEADER = """ | |
**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. 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" | |
d = os.environ.get("DEVICE", None) | |
if d != None: | |
device = d | |
model = TSR.from_pretrained( | |
"stabilityai/TripoSR", | |
config_name="config.yaml", | |
weight_name="model.ckpt", | |
# token=HF_TOKEN | |
) | |
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 | |
def generate(image): | |
scene_codes = model(image, device=device) | |
mesh = model.extract_mesh(scene_codes)[0] | |
mesh = to_gradio_3d_orientation(mesh) | |
mesh_path = tempfile.NamedTemporaryFile(suffix=".obj", delete=False) | |
mesh_path2 = tempfile.NamedTemporaryFile(suffix=".glb", delete=False) | |
mesh.export(mesh_path.name) | |
mesh.export(mesh_path2.name) | |
return mesh_path.name, mesh_path2.name | |
def run_example(image_pil): | |
preprocessed = preprocess(image_pil, False, 0.9) | |
mesh_name, mesn_name2 = generate(preprocessed) | |
return preprocessed, mesh_name, mesh_name2 | |
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, | |
) | |
with gr.Row(): | |
submit = gr.Button("Generate", elem_id="generate", variant="primary") | |
with gr.Column(): | |
with gr.Tab("obj"): | |
output_model = gr.Model3D( | |
label="Output Model", | |
interactive=False, | |
) | |
with gr.Tab("glb"): | |
output_model2 = gr.Model3D( | |
label="Output Model", | |
interactive=False, | |
) | |
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, output_model2], | |
#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], | |
outputs=[output_model, output_model2], | |
) | |
demo.queue(max_size=10) | |
demo.launch() | |