Adamfan/objectdetection

1from fastai.vision.all import *2from io import BytesIO3import requests4import streamlit as st5 6import numpy as np7import torch8import cv29from numpy import random10import os11import sys12 13# 避免模型監聽錯誤14os.environ["STREAMLIT_PREVENT_RUN_ON_SAVE"] = "true"15os.environ["STREAMLIT_WATCHDOG_MODE"] = "none"16os.environ["PYTORCH_NO_OPENCV"] = "1"17 18# 加入 YOLOv7 路徑19sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))20 21from models.experimental import attempt_load22from utils.general import check_img_size, set_logging, non_max_suppression, scale_coords23from utils.plots import plot_one_box24 25# 初始化裝置26set_logging()27device = torch.device("cuda" if torch.cuda.is_available() else "cpu")28 29# Resize and pad image30def letterbox(img, new_shape=(640, 640), color=(114, 114, 114), auto=True, scaleFill=False, scaleup=True, stride=32):31    shape = img.shape[:2]  # [height, width]32    if isinstance(new_shape, int):33        new_shape = (new_shape, new_shape)34 35    r = min(new_shape[0] / shape[0], new_shape[1] / shape[1])36    if not scaleup:37        r = min(r, 1.0)38 39    ratio = r, r40    new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r))41    dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - new_unpad[1]42    if auto:43        dw, dh = np.mod(dw, stride), np.mod(dh, stride)44    elif scaleFill:45        dw, dh = 0.0, 0.046        new_unpad = (new_shape[1], new_shape[0])47        ratio = new_shape[1] / shape[1], new_shape[0] / shape[0]48 49    dw /= 250    dh /= 251 52    if shape[::-1] != new_unpad:53        img = cv2.resize(img, new_unpad, interpolation=cv2.INTER_LINEAR)54    top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))55    left, right = int(round(dw - 0.1)), int(round(dw + 0.1))56    img = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color)57    return img, ratio, (dw, dh)58 59# 預測函式60def detect_modify(img0, model, conf=0.4, imgsz=640, conf_thres=0.25, iou_thres=0.45):61    st.image(img0, caption="原始圖片", use_column_width=True)62 63    # 確保圖像格式正確64    img0 = np.array(img0)65    if img0.ndim == 2:66        img0 = cv2.cvtColor(img0, cv2.COLOR_GRAY2RGB)67    img0 = cv2.cvtColor(img0, cv2.COLOR_RGB2BGR)68 69    stride = int(model.stride.max())70    imgsz = check_img_size(imgsz, s=stride)71    img = letterbox(img0, imgsz, stride=stride)[0]72 73    img = img[:, :, ::-1].transpose(2, 0, 1)74    img = np.ascontiguousarray(img)75    img = torch.from_numpy(img).to(device).float() / 255.076 77    if img.ndimension() == 3:78        img = img.unsqueeze(0)79 80    names = model.module.names if hasattr(model, 'module') else model.names81    colors = [[random.randint(0, 255) for _ in range(3)] for _ in names]82 83    with torch.no_grad():84        pred = model(img)[0]85    pred = non_max_suppression(pred, conf_thres, iou_thres)86 87    det = pred[0]88    if len(det):89        det[:, :4] = scale_coords(img.shape[2:], det[:, :4], img0.shape).round()90        for *xyxy, conf, cls in reversed(det):91            label = f'{names[int(cls)]} {conf:.2f}'92            plot_one_box(xyxy, img0, label=label, color=colors[int(cls)], line_thickness=2)93 94    st.markdown("### 偵測結果：")95    st.image(Image.fromarray(cv2.cvtColor(img0, cv2.COLOR_BGR2RGB)), use_column_width=True)96 97# 模型載入與快取98@st.cache_resource99def load_model():100    current_dir = os.path.dirname(os.path.abspath(__file__))101    weight_path = os.path.join(current_dir, 'best.pt')102    model = attempt_load(weight_path, map_location=device)103    model.eval()104    return model105 106# Streamlit UI 主程式107def main():108    st.title("🧠 YOLOv7 物件偵測 Web 應用")109    st.write("請選擇圖片來源並進行偵測")110 111    model = load_model()112 113    option = st.radio("選擇輸入方式：", ["上傳圖片", "圖片 URL"])114 115    imgsz = 640116    conf = 0.4117    conf_thres = 0.25118    iou_thres = 0.45119 120    if option == "上傳圖片":121        uploaded_file = st.file_uploader("請上傳圖片", type=["jpg", "png", "jpeg"])122        if uploaded_file is not None:123            img = PILImage.create(uploaded_file)124            detect_modify(img, model, conf=conf, imgsz=imgsz, conf_thres=conf_thres, iou_thres=iou_thres)125 126    else:127        url = st.text_input("請輸入圖片 URL：")128        if url:129            try:130                response = requests.get(url)131                img = PILImage.create(BytesIO(response.content))132                detect_modify(img, model, conf=conf, imgsz=imgsz, conf_thres=conf_thres, iou_thres=iou_thres)133            except Exception as e:134                st.error(f"讀取圖片失敗：{e}")135 136if __name__ == "__main__":137    main()138