import numpy as np
import pdb
resScore = np.loadtxt("/home/wangxiao/Downloads/pysot/experiments/siamrpn_r50_l234_dwxcorr_otb/results/response_score/responseScore.txt")
res = np.loadtxt("/home/wangxiao/Downloads/pysot/experiments/siamrpn_r50_l234_dwxcorr_otb/results/siamrpn_resnet50_dwxcorr_otb/Assian_video_Z03_done.txt")
gt_rects = np.loadtxt("/home/wangxiao/Downloads/pysot/experiments/siamrpn_r50_l234_dwxcorr_otb/results/siamrpn_resnet50_dwxcorr_otb/groundtruth.txt")
# pdb.set_trace()
def overlap_ratio(rect1, rect2):
if rect1.ndim==1:
rect1 = rect1[None,:]
if rect2.ndim==1:
rect2 = rect2[None,:]
left = np.maximum(rect1[:,0], rect2[:,0])
right = np.minimum(rect1[:,0]+rect1[:,2], rect2[:,0]+rect2[:,2])
top = np.maximum(rect1[:,1], rect2[:,1])
bottom = np.minimum(rect1[:,1]+rect1[:,3], rect2[:,1]+rect2[:,3])
intersect = np.maximum(0,right - left) * np.maximum(0,bottom - top)
union = rect1[:,2]*rect1[:,3] + rect2[:,2]*rect2[:,3] - intersect
iou = np.clip(intersect / union, 0, 1)
return iou
def compute_success_overlap(gt_bb, result_bb):
thresholds_overlap = np.arange(0, 1.05, 0.05)
n_frame = len(gt_bb)
success = np.zeros(len(thresholds_overlap))
iou = np.zeros(n_frame)
for i in range(n_frame):
iou[i] = overlap_ratio(np.array(gt_bb[i]), np.array(result_bb[i]))
for i in range(len(thresholds_overlap)):
success[i] = sum(iou > thresholds_overlap[i]) / n_frame
# return success
return iou
success_overlap = compute_success_overlap(gt_rects, res)
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
x_data = list(range(gt_rects.shape[0]))
y_data = success_overlap
y_data2 = resScore
# pdb.set_trace()
ln1, = plt.plot(x_data,y_data,color='red',linewidth=2.0,linestyle='-')
ln2, = plt.plot(x_data,y_data2,color='blue',linewidth=2.0,linestyle='-')
plt.title("xxxx")
plt.legend(handles=[ln1,ln2],labels=['IoU Value','Response Score'])
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
plt.show()