def gen_rect_image(): # Generator for yielding (rect,cropped) tuples
image = np.array(Image.open(image_file).convert(mode='RGB'))
rects = data_tools.parse_boxes_from_text(rects_file,slice_first=True)[0]
for rect in rects:
cropped = data_tools.normalize_box(image,rect,**kwargs)
yield rect, cropped
def gen_rect_image(): # Generator for yielding (rect,cropped) tuples
image = cv2.imread(image_file)[:, :, ::-1] # BGR->RGB
rects = data_tools.parse_boxes_from_text(rects_file,
slice_first=True)[0]
for rect in rects:
cropped = data_tools.normalize_box(image, rect, **kwargs)
yield rect, cropped
def main(argv=None):
"""Loads up ground truth and prediction files, calculates and
prints statistics
"""
# Load file lists
prediction_files = data_tools.get_filenames(
FLAGS.pred_path,
str.split(FLAGS.filename_pattern,','),
'txt')
ground_truth_files = data_tools.get_paired_filenames(
prediction_files, FLAGS.gt_path, 'json' )
assert len(ground_truth_files) == len(prediction_files)
# Load files contents and package for stats evaluation
predictions = {}
ground_truths = {}
for pred_file,truth_file in zip(prediction_files,ground_truth_files):
base = os.path.splitext(os.path.basename(pred_file))[0]
[_,gt_polys,gt_labels] = data_tools.parse_boxes_from_json( truth_file )
[_,polys,labels,scores] = data_tools.parse_boxes_from_text( pred_file )
if FLAGS.score_thresh: # Filter predictions if necessary
polys,labels,scores = threshold_predictions(
polys, labels, scores)
predictions[base] = { 'polygons' : polys,
'labels' : labels,
'scores' : scores }
ground_truths[base] = {'polygons' : gt_polys,
'labels' : gt_labels }
# Calculate statistics on predictions for ground truths
sample_stats,total_stats = stats.evaluate_predictions(
ground_truths,
predictions,
match_labels=FLAGS.match_labels,
iou_match_thresh=FLAGS.iou_thresh)
# Display save the results
print sample_stats
print total_stats
if FLAGS.save_result:
import json
with open(os.path.join(FLAGS.pred_path,FLAGS.save_result+'.json'),'w') \
as fd:
json.dump({'individual': sample_stats, 'overall': total_stats}, fd,
indent=4)