| |
|
|
| import streamlit as st |
| import torch |
| from PIL import Image |
| import camera |
| import numpy as np |
| import cv2 |
|
|
| |
| def detect_objects(image_path): |
| model = torch.hub.load('ultralytics/yolov5', 'yolov5s') |
| img = Image.open(image_path) |
| results = model(img) |
| return results |
|
|
| def main(): |
| st.title("摄像头拍照并进行物体识别") |
|
|
| |
| if st.button('拍照'): |
| camera.take_picture() |
| st.write("照片已拍摄并保存") |
|
|
| |
| if st.button('物体识别'): |
| st.write("正在进行物体识别...") |
| image_path = "captured_image.jpg" |
| |
| results = detect_objects(image_path) |
| |
| st.image(image_path, caption='原始图片', use_column_width=True) |
| |
| |
| results.render() |
| detected_img = Image.fromarray(results.imgs[0]) |
|
|
| st.image(detected_img, caption='物体识别结果', use_column_width=True) |
|
|
| |
| st.write("识别到的物体：") |
| objects = results.pandas().xyxy[0]['name'].tolist() |
| objects_sorted_by_x = sorted(objects) |
| st.write(objects_sorted_by_x) |
|
|
| if __name__ == '__main__': |
| main() |
|
|
