def evaluate_proposal_file(dataset, proposal_file, output_dir):
"""Evaluate box proposal average recall."""
roidb = dataset.get_roidb(gt=True, proposal_file=proposal_file)
results = task_evaluation.evaluate_box_proposals(dataset, roidb)
task_evaluation.log_box_proposal_results(results)
recall_file = os.path.join(output_dir, 'rpn_proposal_recall.pkl')
save_object(results, recall_file)
return results
def evaluate_proposal_file(dataset, proposal_file, output_dir):
"""Evaluate box proposal average recall."""
roidb = dataset.get_roidb(gt=True, proposal_file=proposal_file)
results = task_evaluation.evaluate_box_proposals(dataset, roidb)
task_evaluation.log_box_proposal_results(results)
recall_file = os.path.join(output_dir, 'rpn_proposal_recall.pkl')
save_object(results, recall_file)
return results
def evaluate_proposal_file(dataset, proposal_file, output_dir):
"""Evaluate box proposal average recall."""
roidb = dataset.get_roidb(gt=True, proposal_file=proposal_file)
results = task_evaluation.evaluate_box_proposals(dataset, roidb)
task_evaluation.log_box_proposal_results(results)
recall_file = os.path.join(output_dir, 'rpn_proposal_recall.pkl')
save_object(results, recall_file)
all_boxes = np.array([[],
smd.prep_proposal_file(proposal_file,
output_dir,
top_k=100)])
"""Plot Precision Recall curve for proposal file"""
smd.evaluate_boxes(dataset, all_boxes, output_dir)
smd.draw_histos(filepath=output_dir)
"""Plot recall-proposals curve"""
boxes = np.array(all_boxes[1:][0])
scores = boxes[:, :, -1]
boxes = boxes[:, :, :-1]
smd.plot_rec_prop_curve(boxes, scores, dataset, output_dir, n=40)
return results
