app.py

import gradio as gr
from segment_anything import SamAutomaticMaskGenerator, sam_model_registry
import supervision as sv
from inference import DepthPredictor, SegmentPredictor
from utils import create_3d_obj, create_3d_pc
import numpy as np


def snap(image, video):
    depth_predictor = DepthPredictor()
    depth_result = depth_predictor.predict(image)
    gltf_path = create_3d_pc(np.array(image), depth_result)
    #segment_predictor = SegmentPredictor()
    #sam_result = segment_predictor.predict(image)
    return [image, gltf_path, gltf_path]#[depth_result, gltf_path, gltf_path]


demo = gr.Interface(
    snap,
    inputs=[gr.Image(source="webcam", tool=None, type="pil"),
            gr.Video(source="webcam")],
    outputs=[gr.Image(label="predicted depth", type="pil"),
             gr.Model3D(label="3d mesh reconstruction", clear_color=[1.0, 1.0, 1.0, 1.0]), gr.File(label="3d gLTF")]
)

if __name__ == "__main__":
    demo.launch()