summary_name = 'eval/average_precision_voc07' op = tf.summary.scalar(summary_name, ap, collections=[]) op = tf.Print(op, [ap], summary_name) tf.add_to_collection(tf.GraphKeys.SUMMARIES, op) # Split into values and updates ops. names_to_values, names_to_updates = slim.metrics.aggre...
python tracking machine-learning computer-vision deep-learning metrics tensorflow image-processing pytorch video-processing yolo classification coco object-detection hacktoberfest pascal-voc low-code instance-segmentation oriented-bounding-box Updated Dec 2, 2024 Python rafael...
1"""Factory method for easily getting imdbs by name."""2from__future__importabsolute_import3from__future__importdivision4from__future__importprint_function56__sets={}7fromdatasets.pascal_vocimportpascal_voc89importnumpy as np1011#Set up voc_<year>_<split>12foryearin['2007','2012']:13f...
This example shows how to train a semantic segmentation network using deep learning. - KentaItakura/Semantic-segmentation-using-Pascal-VOC-with-MATLAB
A Python library to evaluate mean Average Precision(mAP) for object detection. Provides the same output as PASCAL VOC's matlab code. - RalphMao/VMetrics
To specify the path of the text file that contains class-wise and overall results under lrp and ap metrics. --set: Which set to perform evaluation on. (train, val, test) --year: Which year to perform evaluation on. (i.e.: VOC2007, VOC2012) --comp: Whether to use competition mode...
MethodBenchmark datasetMetrics CornerNetCOCOAP@[.5:.05:.95]; AP@.50; AP@.75; APS; APM; APL EfficientDetCOCOAP@[.5:.05:.95]; AP@.50; AP@.75 Fast R-CNNPASCAL VOC 2007, 2010, 2012AP; mAP (IOU=.50) Faster R-CNNPASCAL VOC 2007, 2012AP; mAP (IOU=.50) ...