OPENCV - 如何使用 Haar 级联 Github xml 文件在 Z5BD4C87976F348E6A5E949?D

Question

I am starting to learn object detection in OpenCV 3.4.2 (.Net C++ 2017). I am very interested in detecting strawberries in pictures (at the moment I am really interested in detecting just strawberries). I know OpenCV has some pre-trained Haar cascade files in OpenCV directory, but there are not.xml files for strawberries (there are for body parts instead).

So I decided to search on Google, to try to find trained strawberry Haar cascade.xml files. I found this.xml file XML strawberry file but I get error -49 when I try to execute the program. I have executed correctly the program using OpenCV files, but I cannot execute correctly when I try with GitHub XML file.

I have found this thread here on StackOverflow StackOverFlow thread about GitHub XML files in OpenCV and a user claims that it's not possible to use GitHub XML files into OpenCV.

My question is about if there is a way to use the XML GitHub file I have posted in this thread in OpenCV or I need to train my own XML file? I would like to use GitHub file.

Edit(1) I have found this link strawberry detection in OpenCV where, if you look at the source code, it seems that the same strawberry_classifier.xml is being used. I don't know if the name of the file is just a coincidence (Github filename and the filename shown in the source code of the 3rd link are exactly the same). At least it seems that the programmer (from the 3rd link) has obtained some results while using the (apparently) same.xml file that I want to use. But I don't know how to use that strawberry_classifier.xml file.

Answer 1

Python dev here, I'm late, but in case anyone still wants to see an answer:

The classifier from GitHub works perfectly fine as shown in this Python code (Sorry, I didn't do it in C++, but I think it won't be much different)

The script uses your webcam as the image source. You can show the webcam some images of strawberries, and it will recognize it:

import cv2 #import library

#define Haar Cascade Classifier
Strawberry_Classifier = cv2.CascadeClassifier(r"C:\Users\Strawberry.xml")
VideoCapture = cv2.VideoCapture(0) #capture video from camera

#set video size
VideoCapture.set(3, 540)
VideoCapture.set(4, 360)

while True:
     #Connect video and convert
     Connection_Success, Video = VideoCapture.read()                              #returns a bool and video array in one tuple (sucess, video array)
     RGB_video = cv2.cvtColor(Video, cv2.COLOR_BGR2RGB)                           #converts to suitable format
     Detect_Strawberry = Strawberry_Classifier.detectMultiScale(RGB_video, 1.3, 13) #MODIFY THIS FOR LESS/MORE DETECTION ACCURACY 

     #Detect Strawberry
     for(x,y,w,h) in Detect_Strawberry: #x,y width, height
          cv2.rectangle(Video, (x, y), (x + w, y + h), (0, 255, 0), 3)                         #Put a rectangle around Strawberry
          
     cv2.imshow("Window", Video) #show video

     #quit if q is pressed, quit
     QuitKey = cv2.waitKey(30)
     if QuitKey == ord("q"):
          VideoCapture.release()
          cv2.destroyAllWindows()