1>>>print(cascade.detectMultiScale.__doc__)2detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]])-> objects
3. @brief Detects objects of different sizes in the input image. The detected objects are returned as a list4. of rectangles.5.6. @param image Matrix of the type CV_8U containing an image where objects are detected.7. @param objects Vector of rectangles where each rectangle contains the detected object, the
8. rectangles may be partially outside the original image.9. @param scaleFactor Parameter specifying how much the image size is reduced at each image scale.10. @param minNeighbors Parameter specifying how many neighbors each candidate rectangle should have
11. to retain it.12. @param flags Parameter with the same meaning for an old cascade asin the function
13. cvHaarDetectObjects. It isnot used for a new cascade.14. @param minSize Minimum possible object size. Objects smaller than that are ignored.15. @param maxSize Maximum possible object size. Objects larger than that are ignored. If `maxSize == minSize` model is evaluated on single scale.16.17. The function is parallelized with the TBB library.18.19. @note
20.-(Python) A face detection example using cascade classifiers can be found at
21. opencv_source_code/samples/python/facedetect.py
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2022/01/17 08:59