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refactor __init__(2)

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lorenzo 2019-05-21 11:11:07 +02:00
parent 6fbc496702
commit 67bc780677
1 changed files with 27 additions and 30 deletions
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57
src/eval/kitti_eval.py
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@ -19,6 +19,8 @@ class KittiEval:
- 3DOP - 3DOP
- MonoDepth - MonoDepth
""" """
dic_stds = defaultdict(lambda: defaultdict(list))
dic_stats = defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(float))))
def __init__(self, show=False, thresh_iou_our=0.3, thresh_iou_m3d=0.5, thresh_conf_m3d=0.5, thresh_conf_our=0.3): def __init__(self, show=False, thresh_iou_our=0.3, thresh_iou_m3d=0.5, thresh_conf_m3d=0.5, thresh_conf_our=0.3):
@ -54,15 +56,10 @@ class KittiEval:
# Extract validation images for evaluation # Extract validation images for evaluation
names_gt = tuple(os.listdir(self.dir_gt)) names_gt = tuple(os.listdir(self.dir_gt))
_, self.set_val = split_training(names_gt, path_train, path_val) _, self.set_val = split_training(names_gt, path_train, path_val)
aa = 5
def run(self): def run(self):
"""Evaluate Monoloco methods on ALP and ALE metrics""" """Evaluate Monoloco methods on ALP and ALE metrics"""
self.dic_stds = defaultdict(lambda: defaultdict(list))
dic_stats = defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(float))))
cnt_gt = 0 cnt_gt = 0
# Iterate over each ground truth file in the training set # Iterate over each ground truth file in the training set
@ -73,7 +70,7 @@ class KittiEval:
path_3dop = os.path.join(self.dir_3dop, name) path_3dop = os.path.join(self.dir_3dop, name)
path_md = os.path.join(self.dir_md, name) path_md = os.path.join(self.dir_md, name)
boxes_gt = [] boxes_gt = []
truncs_gt = [] # Float from 0 to 1 truncs_gt = [] # Float from 0 to 1
occs_gt = [] # Either 0,1,2,3 fully visible, partly occluded, largely occluded, unknown occs_gt = [] # Either 0,1,2,3 fully visible, partly occluded, largely occluded, unknown
dds_gt = [] dds_gt = []
dic_fin = defaultdict(list) dic_fin = defaultdict(list)
@ -81,7 +78,7 @@ class KittiEval:
# Iterate over each line of the gt file and save box location and distances # Iterate over each line of the gt file and save box location and distances
with open(path_gt, "r") as f_gt: with open(path_gt, "r") as f_gt:
for line_gt in f_gt: for line_gt in f_gt:
if self.check_conditions(line_gt, mode='gt'): if check_conditions(line_gt, mode='gt'):
truncs_gt.append(float(line_gt.split()[1])) truncs_gt.append(float(line_gt.split()[1]))
occs_gt.append(int(line_gt.split()[2])) occs_gt.append(int(line_gt.split()[2]))
boxes_gt.append([float(x) for x in line_gt.split()[4:8]]) boxes_gt.append([float(x) for x in line_gt.split()[4:8]])
@ -112,19 +109,19 @@ class KittiEval:
# Save statistics # Save statistics
for key in self.errors: for key in self.errors:
for clst in self.clusters[:-2]: # M3d and pifpaf does not have annotations above 40 meters for clst in self.clusters[:-2]: # M3d and pifpaf does not have annotations above 40 meters
dic_stats['test'][key]['mean'][clst] = sum(self.errors[key][clst]) / float(len(self.errors[key][clst])) self.dic_stats['test'][key]['mean'][clst] = sum(self.errors[key][clst]) / float(len(self.errors[key][clst]))
dic_stats['test'][key]['max'][clst] = max(self.errors[key][clst]) self.dic_stats['test'][key]['max'][clst] = max(self.errors[key][clst])
dic_stats['test'][key]['cnt'][clst] = len(self.errors[key][clst]) self.dic_stats['test'][key]['cnt'][clst] = len(self.errors[key][clst])
if key == 'our': if key == 'our':
for clst in self.clusters[:-2]: for clst in self.clusters[:-2]:
dic_stats['test'][key]['std_ale'][clst] = \ self.dic_stats['test'][key]['std_ale'][clst] = \
sum(self.dic_stds['ale'][clst]) / float(len(self.dic_stds['ale'][clst])) sum(self.dic_stds['ale'][clst]) / float(len(self.dic_stds['ale'][clst]))
dic_stats['test'][key]['std_epi'][clst] = \ self.dic_stats['test'][key]['std_epi'][clst] = \
sum(self.dic_stds['epi'][clst]) / float(len(self.dic_stds['epi'][clst])) sum(self.dic_stds['epi'][clst]) / float(len(self.dic_stds['epi'][clst]))
dic_stats['test'][key]['interval'][clst] = \ self.dic_stats['test'][key]['interval'][clst] = \
sum(self.dic_stds['interval'][clst]) / float(len(self.dic_stds['interval'][clst])) sum(self.dic_stds['interval'][clst]) / float(len(self.dic_stds['interval'][clst]))
dic_stats['test'][key]['at_risk'][clst] = \ self.dic_stats['test'][key]['at_risk'][clst] = \
sum(self.dic_stds['at_risk'][clst]) / float(len(self.dic_stds['at_risk'][clst])) sum(self.dic_stds['at_risk'][clst]) / float(len(self.dic_stds['at_risk'][clst]))
# Print statistics # Print statistics
@ -145,14 +142,14 @@ class KittiEval:
for clst in self.clusters[:-9]: for clst in self.clusters[:-9]:
print(" {} Average error in cluster {}: {:.2f} with a max error of {:.1f}, " print(" {} Average error in cluster {}: {:.2f} with a max error of {:.1f}, "
"for {} annotations" "for {} annotations"
.format(key, clst, dic_stats['test'][key]['mean'][clst], dic_stats['test'][key]['max'][clst], .format(key, clst, self.dic_stats['test'][key]['mean'][clst], self.dic_stats['test'][key]['max'][clst],
dic_stats['test'][key]['cnt'][clst])) self.dic_stats['test'][key]['cnt'][clst]))
if key == 'our': if key == 'our':
print("% of annotation inside the confidence interval: {:.1f} %, " print("% of annotation inside the confidence interval: {:.1f} %, "
"of which {:.1f} % at higher risk" "of which {:.1f} % at higher risk"
.format(100 * dic_stats['test'][key]['interval'][clst], .format(100 * self.dic_stats['test'][key]['interval'][clst],
100 * dic_stats['test'][key]['at_risk'][clst])) 100 * self.dic_stats['test'][key]['at_risk'][clst]))
for perc in ['<0.5m', '<1m', '<2m']: for perc in ['<0.5m', '<1m', '<2m']:
print("{} Instances with error {}: {:.2f} %" print("{} Instances with error {}: {:.2f} %"
@ -162,7 +159,7 @@ class KittiEval:
print("-"*100) print("-"*100)
# Print images # Print images
self.print_results(dic_stats, self.show) print_results(self.dic_stats, self.show)
def parse_txts(self, path, method): def parse_txts(self, path, method):
boxes = [] boxes = []
@ -179,7 +176,7 @@ class KittiEval:
try: try:
with open(path, "r") as ff: with open(path, "r") as ff:
for line in ff: for line in ff:
if self.check_conditions(line, thresh=self.dic_thresh_conf[method], mode=method): if check_conditions(line, thresh=self.dic_thresh_conf[method], mode=method):
boxes.append([float(x) for x in line.split()[4:8]]) boxes.append([float(x) for x in line.split()[4:8]])
loc = ([float(x) for x in line.split()[11:14]]) loc = ([float(x) for x in line.split()[11:14]])
dds.append(math.sqrt(loc[0] ** 2 + loc[1] ** 2 + loc[2] ** 2)) dds.append(math.sqrt(loc[0] ** 2 + loc[1] ** 2 + loc[2] ** 2))
@ -235,7 +232,7 @@ class KittiEval:
file_lines = ff.readlines() file_lines = ff.readlines()
for line_our in file_lines[:-1]: for line_our in file_lines[:-1]:
line_list = [float(x) for x in line_our.split()] line_list = [float(x) for x in line_our.split()]
if self.check_conditions(line_list, thresh=self.dic_thresh_conf[method], mode=method): if check_conditions(line_list, thresh=self.dic_thresh_conf[method], mode=method):
boxes.append(line_list[:4]) boxes.append(line_list[:4])
xyzs.append(line_list[4:7]) xyzs.append(line_list[4:7])
dds.append(line_list[7]) dds.append(line_list[7])
@ -264,8 +261,8 @@ class KittiEval:
for idx, box in enumerate(boxes): for idx, box in enumerate(boxes):
if len(boxes_gt) >= 1: if len(boxes_gt) >= 1:
dd = dds[idx] dd = dds[idx]
idx_max, iou_max = self.get_idx_max(box, boxes_gt) idx_max, iou_max = get_idx_max(box, boxes_gt)
cat = self.get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max]) cat = get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max])
# Update error if match is found # Update error if match is found
if iou_max > self.dic_thresh_iou[method]: if iou_max > self.dic_thresh_iou[method]:
dd_gt = dds_gt[idx_max] dd_gt = dds_gt[idx_max]
@ -295,8 +292,8 @@ class KittiEval:
epi = stds_epi[idx] epi = stds_epi[idx]
xyz = xyzs[idx] xyz = xyzs[idx]
xy_kp = xy_kps[idx] xy_kp = xy_kps[idx]
idx_max, iou_max = self.get_idx_max(box, boxes_gt) idx_max, iou_max = get_idx_max(box, boxes_gt)
cat = self.get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max]) cat = get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max])
# Update error if match is found # Update error if match is found
if iou_max > self.dic_thresh_iou['our']: if iou_max > self.dic_thresh_iou['our']:
@ -340,12 +337,12 @@ class KittiEval:
if len(boxes_gt) >= 1: if len(boxes_gt) >= 1:
dd_our = dds_our[idx] dd_our = dds_our[idx]
dd_geom = dds_geom[idx] dd_geom = dds_geom[idx]
idx_max, iou_max = self.get_idx_max(box, boxes_gt) idx_max, iou_max = get_idx_max(box, boxes_gt)
cat = self.get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max]) cat = get_category(boxes_gt[idx_max], truncs_gt[idx_max], occs_gt[idx_max])
idx_max_3dop, iou_max_3dop = self.get_idx_max(box, boxes_3dop) idx_max_3dop, iou_max_3dop = get_idx_max(box, boxes_3dop)
idx_max_m3d, iou_max_m3d = self.get_idx_max(box, boxes_m3d) idx_max_m3d, iou_max_m3d = get_idx_max(box, boxes_m3d)
idx_max_md, iou_max_md = self.get_idx_max(box, boxes_md) idx_max_md, iou_max_md = get_idx_max(box, boxes_md)
iou_min = min(iou_max_3dop, iou_max_m3d, iou_max_md) iou_min = min(iou_max_3dop, iou_max_m3d, iou_max_md)