本文整理汇总了Python中keras_frcnn.data_generators.iou方法的典型用法代码示例。如果您正苦于以下问题：Python data_generators.iou方法的具体用法？Python data_generators.iou怎么用？Python data_generators.iou使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类keras_frcnn.data_generators的用法示例。
在下文中一共展示了data_generators.iou方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_map
# 需要导入模块: from keras_frcnn import data_generators [as 别名]
# 或者: from keras_frcnn.data_generators import iou [as 别名]
def get_map(pred, gt, f):
T = {}
P = {}
fx, fy = f
for bbox in gt:
bbox['bbox_matched'] = False
pred_probs = np.array([s['prob'] for s in pred])
box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]
for box_idx in box_idx_sorted_by_prob:
pred_box = pred[box_idx]
pred_class = pred_box['class']
pred_x1 = pred_box['x1']
pred_x2 = pred_box['x2']
pred_y1 = pred_box['y1']
pred_y2 = pred_box['y2']
pred_prob = pred_box['prob']
if pred_class not in P:
P[pred_class] = []
T[pred_class] = []
P[pred_class].append(pred_prob)
found_match = False
for gt_box in gt:
gt_class = gt_box['class']
gt_x1 = gt_box['x1']/fx
gt_x2 = gt_box['x2']/fx
gt_y1 = gt_box['y1']/fy
gt_y2 = gt_box['y2']/fy
gt_seen = gt_box['bbox_matched']
if gt_class != pred_class:
continue
if gt_seen:
continue
iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
if iou >= 0.5:
found_match = True
gt_box['bbox_matched'] = True
break
else:
continue
T[pred_class].append(int(found_match))
for gt_box in gt:
if not gt_box['bbox_matched'] and not gt_box['difficult']:
if gt_box['class'] not in P:
P[gt_box['class']] = []
T[gt_box['class']] = []
T[gt_box['class']].append(1)
P[gt_box['class']].append(0)
#import pdb
#pdb.set_trace()
return T, P 示例2: get_map
# 需要导入模块: from keras_frcnn import data_generators [as 别名]
# 或者: from keras_frcnn.data_generators import iou [as 别名]
def get_map(pred, gt, f):
T = {}
P = {}
fx, fy = f
for bbox in gt:
bbox['bbox_matched'] = False
pred_probs = np.array([s['prob'] for s in pred])
box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]
for box_idx in box_idx_sorted_by_prob:
pred_box = pred[box_idx]
pred_class = pred_box['class']
pred_x1 = pred_box['x1']
pred_x2 = pred_box['x2']
pred_y1 = pred_box['y1']
pred_y2 = pred_box['y2']
pred_prob = pred_box['prob']
if pred_class not in P:
P[pred_class] = []
T[pred_class] = []
P[pred_class].append(pred_prob)
found_match = False
for gt_box in gt:
gt_class = gt_box['class']
gt_x1 = gt_box['x1']/fx
gt_x2 = gt_box['x2']/fx
gt_y1 = gt_box['y1']/fy
gt_y2 = gt_box['y2']/fy
gt_seen = gt_box['bbox_matched']
if gt_class != pred_class:
continue
if gt_seen:
continue
iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
if iou >= 0.5:
found_match = True
gt_box['bbox_matched'] = True
break
else:
continue
T[pred_class].append(int(found_match))
for gt_box in gt:
if not gt_box['bbox_matched'] and not gt_box['difficult']:
if gt_box['class'] not in P:
P[gt_box['class']] = []
T[gt_box['class']] = []
T[gt_box['class']].append(1)
P[gt_box['class']].append(0)
#import pdb
#pdb.set_trace()
return T, P