![]() ![]() detectAndDecode ( img = img ) pyzbar_out = pyzbar_reader ( image = img ) # Read the content of the pyzbar output (double decoding will save you from a lot of wrongly decoded characters) pyzbar_out = tuple ( out. detect_and_decode ( image = img ) cv2_out = cv2_reader. from qreader import QReader from cv2 import QRCodeDetector, imread from pyzbar.pyzbar import decode # Initialize the three tested readers (QRReader, OpenCV and pyzbar) qreader_reader, cv2_reader, pyzbar_reader = QReader (), QRCodeDetector (), decode for img_path in ( 'test_mobile.jpeg', 'test_draw_64圆4.jpeg' ): # Read the image img = imread ( img_path ) # Try to decode the QR code with the three readers qreader_out = qreader_reader. The following code will try to decode these images containing QRs with QReader, pyzbar and OpenCV. At right, a 64圆4 QR pasted over a drawing. At left, an image taken with a mobile phone. If no QR code can be decoded, it will return None. If None, it will look for the QR code in the whole image (not recommended). The bounding box of the QR code in the format ( x1, y1, x2, y2). Internally, this method will run the pyzbar decoder, using different image preprocessing techniques ( sharpening, binarization, blurring.) every time it fails to increase the detection rate.ībox: tuple | None. This method decodes a single QR code on the given image, if a bbox is given (recommended) it will only look within that delimited region. NOTE: This the only function you will need? Take a look at QRDet. The image must is expected to be in uint8 format, RGB. NumPy Array containing the image to decode. This method detects the QR codes in the image and returns the bounding boxes surrounding them in the format ( x1, y1, x2, y2). If return_bboxes is False, the output will look like: ('Decoded QR 1', 'Decoded QR 2', None, 'Decoded QR 4'. Returns: tuple | tuple, str | None]]: A tuple with all detected QR codes decodified. If True, it will also return the bboxes of each detected QR. The image is expected to be in uint8 format, RGB. This method will decode the QR codes in the given image and return the decoded strings (or None, if any of them could be detected but not decoded). API Reference tect_and_decode(image, return_bboxes = False) NOTE: Some entries can be None, it will happen when a QR have been detected but couldn't be decoded. detect_and_decode ( image = image )ĭetect_and_decode will return a tuple containing the decoded string of every QR found in the image. COLOR_BGR2RGB ) # Use the detect_and_decode function to get the decoded QR data decoded_text = qreader. For most use cases, you'll only need to call detect_and_decode: from qreader import QReader import cv2 # Create a QReader instance qreader = QReader () # Get the image that contains the QR code (QReader expects an uint8 numpy array) image = cv2. QReader is a very simple and straight-forward library. To do so, run: pip install torch -no-cache-dir (Thanks to for his advice). NOTE: If you're running QReader in a server with very limited resources, you may want to install the CPU version of PyTorch, before installing QReader. ![]() ![]() If you're not using Windows, you may need to install some additional pyzbar dependencies: To install QReader, simply run: pip install qreader On top of Pyzbar, QReader transparently applyes different image preprocessing techniques that maximize the decoding rate on difficult images. Powered by a YOLOv7 model.īehind the scenes, the library is composed by two main building blocks: A QR Detector based on a YOLOv7 model trained on a large dataset of QR codes (also offered as stand-alone), and the Pyzbar QR Decoder. QReader is a Robust and Straight-Forward solution for reading difficult and tricky QR codes within images in Python.
0 Comments
Leave a Reply. |