def visualize_top_predicted_bbox(self, pred_sample, coco_image_dir):
"""Visualize the top predicted bounding box."""
assert 'annotation_id' in pred_sample, 'Object annotation id missing!'
assert 'predicted_bounding_boxes' in pred_sample, \
'list of predicted bounding boxes missing!'
if not pred_sample['predicted_bounding_boxes']:
print 'Empty predicted bounding boxes.'
return
bbox_pred_top = pred_sample['predicted_bounding_boxes'][0]
ann_id = pred_sample['annotation_id']
ann = self.refexp_dataset.loadAnns(ids=[ann_id])[0]
image_id = ann['image_id']
img_coco = self.refexp_dataset.loadImgs(ids=[image_id])[0]
iou = cu.iou_bboxes(bbox_pred_top, ann['bbox'])
if 'refexp' in pred_sample or 'refexp_id' in pred_sample:
print 'The Referring expression input to the model is:'
if 'refexp' in pred_sample:
print ' ' + pred_sample['refexp']
else:
refexp_tmp = self.refexp_dataset.loadRefexps(ids=pred_sample['refexp_id'])[0]
print ' ' + refexp_tmp['raw']
I = misc.imread(os.path.join(coco_image_dir, (img_coco['file_name'])))
ax = plt.imshow(I)
ax = plt.axis('off')
ax = plt.title('IoU: %.3f, green bbox: GT, red bbox: predicted' % iou)
cu.draw_bbox(plt.gca(), ann['bbox'], edge_color='green')
cu.draw_bbox(plt.gca(), bbox_pred_top, edge_color='red')
def visualize_top_predicted_bbox(self, pred_sample, coco_image_dir):
"""Visualize the top predicted bounding box."""
assert 'annotation_id' in pred_sample, 'Object annotation id missing!'
assert 'predicted_bounding_boxes' in pred_sample, \
'list of predicted bounding boxes missing!'
if not pred_sample['predicted_bounding_boxes']:
print 'Empty predicted bounding boxes.'
return
bbox_pred_top = pred_sample['predicted_bounding_boxes'][0]
ann_id = pred_sample['annotation_id']
ann = self.refexp_dataset.loadAnns(ids=[ann_id])[0]
image_id = ann['image_id']
img_coco = self.refexp_dataset.loadImgs(ids=[image_id])[0]
iou = cu.iou_bboxes(bbox_pred_top, ann['bbox'])
if 'refexp' in pred_sample or 'refexp_id' in pred_sample:
print 'The Referring expression input to the model is:'
if 'refexp' in pred_sample:
print ' ' + pred_sample['refexp']
else:
refexp_tmp = self.refexp_dataset.loadRefexps(
ids=pred_sample['refexp_id'])[0]
print ' ' + refexp_tmp['raw']
I = misc.imread(os.path.join(coco_image_dir, (img_coco['file_name'])))
ax = plt.imshow(I)
ax = plt.axis('off')
ax = plt.title('IoU: %.3f, green bbox: GT, red bbox: predicted' % iou)
cu.draw_bbox(plt.gca(), ann['bbox'], edge_color='green')
cu.draw_bbox(plt.gca(), bbox_pred_top, edge_color='red')
def showRegionCandidates(self, image, ax=None):
"""
Display the region candidates for the given image.
:param imgId (int): image id for which we display region candidates
:param ax: matplotlib axes to draw on, or if unspecified, the current axis from `plt.gca()`
:return: None
"""
import matplotlib.pyplot as plt
if ax is None:
ax = plt.gca()
candidates = image['region_candidates']
for candidate in candidates:
bbox = candidate['bounding_box']
draw_bbox(ax, bbox, edge_color='blue')
def showRegionCandidates(self, image, ax=None):
"""
Display the region candidates for the given image.
:param imgId (int): image id for which we display region candidates
:param ax: matplotlib axes to draw on, or if unspecified, the current axis from `plt.gca()`
:return: None
"""
import matplotlib.pyplot as plt
if ax is None:
ax = plt.gca()
candidates = image['region_candidates']
for candidate in candidates:
bbox = candidate['bounding_box']
draw_bbox(ax, bbox, edge_color='blue')
def showAnn(self, ann, ax=None, printRefexps=True):
"""
Display the bbox and referring expressions of the given annotation.
For segmentation display refer to COCO toolkit.
:param anns (array of object): annotations to display
:return: None
"""
import matplotlib.pyplot as plt
if ax is None:
ax = plt.gca()
bbox = ann['bbox']
draw_bbox(ax, bbox, edge_color='green')
if printRefexps:
print('Referring expressions for the object in the bounding box: ')
for ref_id in ann['refexp_ids']:
print(self.dataset['refexps'][ref_id]['raw'])
def showAnn(self, ann, ax=None, printRefexps=True):
"""
Display the bbox and referring expressions of the given annotation.
For segmentation display refer to COCO toolkit.
:param anns (array of object): annotations to display
:return: None
"""
import matplotlib.pyplot as plt
if ax is None:
ax = plt.gca()
bbox = ann['bbox']
draw_bbox(ax, bbox, edge_color='green')
if printRefexps:
print('Referring expressions for the object in the bounding box: ')
for ref_id in ann['refexp_ids']:
print(self.dataset['refexps'][ref_id]['raw'])
