Sep-17-2019, 08:18 PM
(This post was last modified: Sep-17-2019, 08:18 PM by samtwilliams.)
didn't really expose much, I removed that line and went with ndarray;
#cv2.imshow(WINDOW_NAME, frame) #ret, enc = cv2.imencode("*.jpg", frame) results = alpr.recognize_ndarray(frame) print(results)this is the output
Output:root@a6d9d4883914:/anpr# python3 readstream.py
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751373946, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 109.541199, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751374089, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 124.764801, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751374244, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 80.463402, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751374989, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 84.739304, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751375821, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 68.119301, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751376661, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 91.671898, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751377485, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 86.435303, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751378316, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 74.5457, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751379148, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 85.642502, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751379980, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 76.310799, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751380813, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 95.191399, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751381644, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 109.487602, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751382476, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 105.507004, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751383305, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 108.853699, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751384140, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 118.1707, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751384973, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 106.439697, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751385804, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 79.0336, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
{'version': 2, 'data_type': 'alpr_results', 'epoch_time': 1568751386636, 'img_width': 1280, 'img_height': 720, 'processing_time_ms': 105.540497, 'regions_of_interest': [{'x': 0, 'y': 0, 'width': 1280, 'height': 720}], 'results': []}
Fatal Python error: Segmentation fault
Current thread 0x00007f76c0bcc740 (most recent call first):
File "/usr/local/lib/python3.6/dist-packages/openalpr/openalpr.py", line 192 in recognize_ndarray
File "readstream.py", line 54 in main
File "readstream.py", line 88 in <module>
Segmentation fault