物體識別圖形界面小應用

先上效果圖：

 

 

用的python tkinter，識別的模型使用yolov3.

我另一篇博客寫了如何使用yolov3去detect object，這篇博客作爲其桌面化的延伸。

yolov3使用：https://blog.csdn.net/Yonggie/article/details/104964674

因爲邏輯很簡單，所以直接上代碼：

import cv2
import numpy as np
import tkinter as tk
import tkinter.filedialog
from PIL import Image,ImageTk

class Engine:
    def __init__(self):
        self.img=None
        self.model=None
        self.colors=None
        self.output_layers=None
        self.classes=None
        self.path=None

    def LoadModel(self):
        # load yolo
        base = r"G:/Code/YOLO recognition/"
        self.model = cv2.dnn.readNet(base + "yolov3.weights", base + "yolov3.cfg")
        # load label
        with open(base + "coco.names") as f:
            self.classes = [line.strip() for line in f]

        layer_names = self.model.getLayerNames()
        self.output_layers = [layer_names[i[0] - 1] for i in self.model.getUnconnectedOutLayers()]

    def GetPath(self,path):
        self.path=path

    def GetImg(self):

        if self.path is None:
            path_label.config(text='您還沒有選擇圖片！')
            return
        try:
            self.img = cv2.imread(self.path)
        except:
            path_label.config(text='不能打開所選圖片！')
            return

        self.img = cv2.resize(self.img, None, fx=0.4, fy=0.4)

        cv2.imshow("original", self.img)


    def Modify(self):
        if self.img is None:
            return
        self.colors=np.random.uniform(0, 255, size=(len(self.classes), 3))
        img_height, img_width, channel = self.img.shape
        blob = cv2.dnn.blobFromImage(self.img, 0.00392, (416, 416), (0, 0, 0), True, crop=False)

        self.model.setInput(blob)
        outs = self.model.forward(self.output_layers)
        confidences = []
        boxes = []
        pred_indeces = []
        # show info on pic
        for out in outs:
            for detection in out:
                # why after 5
                scores = detection[5:]
                pred_index = np.argmax(scores)
                confidence = scores[pred_index]

                if confidence > 0.5:

                    center_x = int(detection[0] * img_width)
                    center_y = int(detection[1] * img_height)
                    rec_width = int(detection[2] * img_width)
                    rec_height = int(detection[3] * img_height)

                    left_top_x = int(center_x - rec_width / 2)
                    left_top_y = int(center_y - rec_height / 2)

                    boxes.append([left_top_x, left_top_y, rec_width, rec_height])
                    pred_indeces.append(pred_index)
                    confidences.append(float(confidence))


        indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)

        font = cv2.FONT_HERSHEY_PLAIN
        for i in range(len(boxes)):
            if i in indexes:
                left_top_x, left_top_y, rec_width, rec_height = boxes[i]
                label = self.classes[pred_indeces[i]]
                color = self.colors[i]
                cv2.rectangle(self.img, (left_top_x, left_top_y), (left_top_x + rec_width, left_top_y + rec_height), color, 2)
                cv2.putText(self.img, label, (left_top_x, left_top_y + 30), font, 1, color, 2)

    def ShowRes(self):
        if self.img is None:
            return
        cv2.imshow("detected",self.img)

def Detect():
    #get picture
    engine.GetImg()
    engine.Modify()
    engine.ShowRes()


def SelectPic():
    filename = tk.filedialog.askopenfilename()
    if filename != '':
        path_label.config(text = "您選擇的文件是："+filename)
        engine.GetPath(filename)
    else:
        path_label.config(text = "您沒有選擇任何文件")

def center_window(w,h):
    ws = window.winfo_screenwidth()
    hs = window.winfo_screenheight()
    # 計算 x, y 位置
    x = (ws / 2) - (w / 2)
    y = (hs / 2) - (h / 2)
    window.geometry('%dx%d+%d+%d' % (w, h, x, y))

if __name__ == '__main__':
    window=tk.Tk()
    window.title("object detection")
    center_window(500,250)
    window.iconbitmap('detect.ico')

    # cv2.moveWindow("winname", x, y)

    engine=Engine()
    engine.LoadModel()

    path_label=tk.Label(window,text='select a picture:')
    path_label.pack()
    select_button=tk.Button(window, text='select', command=SelectPic)
    select_button.pack()

    empty_label1 = tk.Label(window, text='')
    empty_label1.pack()

    button=tk.Button(window,
            text='detect object',
            width=13,height=1,
            command=Detect)
    button.pack()

    empty_label2 = tk.Label(window, text='')
    empty_label2.pack()

    img=Image.open('background.png')
    img = img.resize((100, 100), Image.ANTIALIAS)
    img=ImageTk.PhotoImage(img)
    img_label=tk.Label(window,image=img)
    img_label.pack()

    tk.mainloop()