app.py

from detecto import core, utils, visualize
from detecto.visualize import show_labeled_image, plot_prediction_grid
from torchvision import transforms
import matplotlib.pyplot as plt
from tensorflow.keras.utils import img_to_array
import numpy as np
import warnings
import streamlit as st
warnings.filterwarnings("ignore", category=UserWarning) 




MODEL_PATH = "SD_model_weights.pth"
IMAGE_PATH = "img1.jpeg"
model = core.Model.load(MODEL_PATH, ['cross_arm','pole','tag'])
#warnings.warn(msg)

st.title("Object Detection")


def detect_object(IMAGE_PATH)
    image = utils.read_image(IMAGE_PATH) 
    predictions = model.predict(image)
    labels, boxes, scores = predictions


    thresh=0.2
    filtered_indices=np.where(scores>thresh)
    filtered_scores=scores[filtered_indices]
    filtered_boxes=boxes[filtered_indices]
    num_list = filtered_indices[0].tolist()
    filtered_labels = [labels[i] for i in num_list]
    visualize.show_labeled_image(image, filtered_boxes, filtered_labels)
    #img_array = img_to_array(img)