If True, it will also return the bboxes of each detected QR. The image is expected to be in uint8 format, RGB. NumPy Array containing the image to decode. 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). tect_and_decode(image, return_bboxes = False) 'cp65001' for Asian languages (Thanks to for the suggestion).Recommendations that have been found useful:
File host qreader code#
If you find some characters being decoded incorrectly, try to set a Code Page that matches your specific charset. The encoding to reencode the utf-8 decoded QR string. Please, try to instantiate it just once to avoid loading the model every time API Reference QReader(reencode_to = 'shift-jis') 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.
File host qreader install#
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. If return_confidences is False it will look like: ((x1, y1, x2, y2). If return_confidences is True, the output will look like: (((x1, y1, x2, y2), confidence). ] | tuple]: A tuple with the coordinates of all detected QR codes. Otherwise, it will be expected to be RGB. If True the image is expected to be in BGR. Otherwise, they will be rounded to the closest integer. If True, the returned coordinates will be returned as float, with the complete precision outputted from the detection model. Otherwise, it will be in the format ((x1, y1, x2, y2). If True, the output will be in the format (((x1, y1, x2, y2), confidence). The image is expected to be in uint8 format, RGB or BGR depending on the is_bgr parameter. imwrite ( filename = 'resources/qreader_test_image_detections.jpeg', img = image ) API Reference tect(image, return_confidences = True, as_float = False, is_bgr = False) FONT_HERSHEY_SIMPLEX, fontScale = 1, color = ( 0, 255, 0 ), thickness = 2 ) # Save the results cv2. putText ( image, f ' ', ( x1, y1 - 10 ), fontFace = cv2. detect ( image = image, is_bgr = True ) # Draw the detections for ( x1, y1, x2, y2 ), confidence in detections : cv2. imread ( filename = 'resources/qreader_test_image.jpeg' ) detections = detector. There is only one function you'll need to call to use QRDet, detect: from qrdet import QRDetector import cv2 detector = QRDetector () image = cv2. To install QRDet, simply run: pip install qrdet If you are looking for a complete QR Detection + Decoding pipeline, take a look at QReader. QRDet will detect QR codes even in difficult positions or tricky images. QRDet is a robust QR Detector based on YOLOv7.
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