app.py

import numpy as np
import matplotlib.pyplot as plt
import cv2
import torch
from segment_anything import sam_model_registry, SamPredictor
from preprocess import show_mask, show_points, show_box
import gradio as gr

def get_coord_infer(evt: gr.SelectData):
    return [evt.index[0], evt.index[1]]

# sam_checkpoint = "weights/sam_vit_b_01ec64.pth"
# model_type = "vit_b"
# device = "cuda" if torch.cuda.is_available() else "cpu"
# sam = sam_model_registry[model_type](checkpoint=sam_checkpoint)
# sam.to(device=device)
# predictor = SamPredictor(sam)

my_app = gr.Blocks()
with my_app:
    gr.Markdown("Segment Anything Testing")
    with gr.Tabs():
        with gr.TabItem("Select your image"):
            with gr.Row():
                with gr.Column():
                    img_source = gr.Image(label="Please select picture.", value='./images/truck.jpg', shape=(768, 768))
                    coords = gr.Label(label="Image Coordinate.")
                with gr.Column():
                    img_output = gr.Image(label="Output Mask")
                    
        img_source.select(get_coord_infer, [], coords)
        # set_point.click(
        #     img_source.select(get_coord),
        #     [
        #         img_source
        #     ],
        #     [
        #         coords
        #     ]
        # )
    
my_app.launch(debug=True)