panorama = return frame, frame_cp return self. shape + 10 ] # Stitch imagesįrame = concat_images () frame_cp = concat_images () # Re-detect barcodes from the new image shape + 10 ] preFrameCp = preFrameCp, 0 : max ( prePoints, prePoints, prePoints, prePoints ) + 10 ] frame_cp = frame_cp, max ( points, points, points, points ): frame_cp. PreFrame = preFrame, 0 : max ( prePoints, prePoints, prePoints, prePoints ) + 10 ] frame = frame, max ( points, points, points, points ): frame. localization_points # Crop image based on min area rect pop () for preResult in preResults : if preResult. panorama while len ( results ) > 0 : result = results. If there is an intersection, transform and stitch. append (( frame, results, frame_cp )) else : # Compare results. FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 )) # Save frame and barcode info if panorama is empty copy () for result in results : points = result. Keep original frame clean.įrame_cp = frame. decode_buffer ( frame ) if results != None : # Draw results on the copy of the frame. We crop the duplicate part of the image and concatenate the remaining part:ĭef stitch_frame ( self, frame ): try : results = self. The code logic is changed to compare barcode and QR code results between adjacent images. The panorama image is generated by concatenating multiple barcode and QR code images. Our focus is on barcode and QR code detection. In case of a product is missing, we can utilize a panorama image, on which we can draw bounding boxes to indicate the missing product.Ĭonsidering the scenario is specific to warehouse robotics, we do not need to put effort on the image stitching, because the camera is moving at a constant speed and the image is stable. A robot with camera can scan barcode and QR code for checking the product status and inventory. Run the code to get the panorama stitching result.īarcode and QR Code Based Image Concatenation for Automated Inventory Managementīarcode and QR code are widely used in modern warehouse inventory management. stitch_frame, ( frame_cp, )) panoramaTask. imshow ( 'panorama', image ) if len ( panoramaTask ) < threadn : task = panoramaPool. count_barcodes ( image ) if count_stitch > total or count_stitch 0 and panoramaTask. panorama : total += count count_stitch = self. save_frame ( all_images ) print ( 'Stitching is done.' ) return None # Drop the stitched image if its quality is not good enough panorama else : # Stop stitching if the output image is out of control Stitcher_OK : print ( "Can't stitch images, error code = %d" % status ) return self. ' ) try : all_images = status, image = self. append (( frame, len ( results ))) print ( 'Stitching. decode_buffer ( frame ) if results != None : for result in results : points = result. PanoramaPool = ThreadPool ( processes = threadn ) panoramaTask = deque () def stitch_frame ( self, frame ): try : results = self.
#Python qr code reader webcam how to
OpenCV repository contains a stitching.py file showing how to use the OpenCV stitcher API. Experiment On Image Stitching and Scanning Multiple QR Codes in a Batch Stitching Multiple Barcode and QR Code Images into a Panorama To solve this problem, we get camera closer to get high quality image for scanning, and then use OpenCV stitching API to stitch multiple barcode and QR code images into a panorama. In this way, the barcode and QR code may become too small to read. As you can see in the above image, to capture all barcode and QR code, we need to increase the lens depth of field. However, the image quality affects the detection accuracy. waitKey ( 1 ) if ch = 27 : breakĭynamsoft Barcode Reader can detect multiple barcodes and QR codes from a single image. imshow ( 'Barcode & QR Code Scanner', frame ) ch = cv. FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 )) if len ( barcodeTasks ) < threadn : task = pool. get () if results != None : for result in results : points = result. read () while len ( barcodeTasks ) > 0 and barcodeTasks. decode_buffer ( frame ) except BarcodeReaderError as bre : print ( bre ) return results while True : ret, frame = cap. Def process_frame ( frame ): results = None try : results = reader.
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