Closed sushanth-d closed 4 years ago
It looks like line 45 in the script is returning None
:
decoded_dict = data_parser.parse(example)
I'd recommend checking that and see why it might be happening.
Hi svpino, i got the same sushanth-d issu and decoded_dict = data_parser.parse(example) returns None, what could u suggest me?
@biakota I got this error because I had not converted the tfrecord by running the following command.
A detection record file — This is the file generated by using the /object_detection/inference/infer_detections.py script. This script runs a TFRecord file through your model and saves the results in a detection record file.
Doing this fixed the error.
@biakota I got this error because I had not converted the tfrecord by running the following command.
A detection record file — This is the file generated by using the /object_detection/inference/infer_detections.py script. This script runs a TFRecord file through your model and saves the results in a detection record file.
Doing this fixed the error.
thank a lot @sushanth-d, i just fixed, you are right, i noticed i forgot to run /object_detection/inference/infer_detections.py first before to run the confusion matrix script
Closing the issue
Hi, I got the same issue although I generated detections_record by using the python inference/infer_detections.py --input_tfrecord_paths=C:/Tensorflow1/models/research/object_detection/test.record --output_tfrecord_path=C:/Tensorflow1/models/research/object_detection/inference_graph/detections8.tfrecord --inference_graph=C:/Tensorflow1/models/research/object_detection/inference_graph/frozen_inference_graph.pb. Could you please help me to solve this issue? @sushanth-d @biakota Thanks.
Could you please help me to solve above issue? Thanks
Hey When I execute the code, the following message is displayed:
Skipped image 1 Skipped image 2 Skipped image 3 Skipped image 4 Skipped image 5 Processed 5 images
Confusion Matrix: [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
confusion_matrix.py:112: RuntimeWarning: invalid value encountered in double_scalars precision = float(confusion_matrix[id, id] / total_predicted) confusion_matrix.py:113: RuntimeWarning: invalid value encountered in double_scalars recall = float(confusion_matrix[id, id] / total_target) precision_threaded@0.5IOU: nan recall_threaded@0.5IOU: nan precision_ungalvanized@0.5IOU: nan recall_ungalvanized@0.5IOU: nan precision_unthreaded@0.5IOU: nan recall_unthreaded@0.5IOU: nan
As seen above, the images are simply skipped, as a result of which the values of classification matrix and precision is erroneous.
Any help will be much appreciated.