def load_annotations_det(self):
ret = []
if not self.validate_det_choices():
return ret, False
if self.rad_det_format_coco_json.isChecked():
ret = converter.coco2bb(self.dir_dets, bb_type=BBType.DETECTED)
elif self.rad_det_ci_format_text_xywh_rel.isChecked(
) or self.rad_det_cn_format_text_xywh_rel.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.RELATIVE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_cn_format_text_xyx2y2_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYX2Y2,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xywh_abs.isChecked(
) or self.rad_det_cn_format_text_xywh_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
# If detection requires class_id, replace the detection names (integers) by a class from the txt file
if self.rad_det_ci_format_text_xywh_rel.isChecked(
) or self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_ci_format_text_xywh_abs.isChecked():
ret = self.replace_id_with_classes(ret, self.filepath_classes_det)
return ret, True
def test_case_1():
gts_dir = 'tests/test_case_1/gts'
dets_dir = 'tests/test_case_1/dets'
gts = converter.text2bb(gts_dir, BBType.GROUND_TRUTH)
dets = converter.text2bb(dets_dir, BBType.DETECTED)
assert (len(gts) > 0)
assert (len(dets) > 0)
testing_ious = [0.1, 0.3, 0.5, 0.75]
# ELEVEN_POINT_INTERPOLATION
expected_APs = {'object': {0.1: 0.3333333333, 0.3: 0.2683982683, 0.5: 0.0303030303, 0.75: 0.0}}
for idx, iou in enumerate(testing_ious):
results_dict = get_pascalvoc_metrics(
gts, dets, iou_threshold=iou, method=MethodAveragePrecision.ELEVEN_POINT_INTERPOLATION)
results = results_dict['per_class']
for c, res in results.items():
assert isclose(expected_APs[c][iou], res['AP'])
# EVERY_POINT_INTERPOLATION
expected_APs = {'object': {0.1: 0.3371980676, 0.3: 0.2456866804, 0.5: 0.0222222222, 0.75: 0.0}}
for idx, iou in enumerate(testing_ious):
results_dict = get_pascalvoc_metrics(
gts, dets, iou_threshold=iou, method=MethodAveragePrecision.EVERY_POINT_INTERPOLATION)
results = results_dict['per_class']
for c, res in results.items():
assert isclose(expected_APs[c][iou], res['AP'])
def load_annotations_gt(self):
ret = []
if self.rad_gt_format_coco_json.isChecked():
ret = converter.coco2bb(self.dir_annotations_gt)
elif self.rad_gt_format_cvat_xml.isChecked():
ret = converter.cvat2bb(self.dir_annotations_gt)
elif self.rad_gt_format_openimages_csv.isChecked():
ret = converter.openimage2bb(self.dir_annotations_gt,
self.dir_images_gt,
BBType.GROUND_TRUTH)
elif self.rad_gt_format_labelme_xml.isChecked():
ret = converter.labelme2bb(self.dir_annotations_gt)
elif self.rad_gt_format_pascalvoc_xml.isChecked():
ret = converter.vocpascal2bb(self.dir_annotations_gt)
elif self.rad_gt_format_imagenet_xml.isChecked():
ret = converter.imagenet2bb(self.dir_annotations_gt)
elif self.rad_gt_format_abs_values_text.isChecked():
ret = converter.text2bb(self.dir_annotations_gt,
bb_type=BBType.GROUND_TRUTH)
elif self.rad_gt_format_yolo_text.isChecked():
ret = converter.yolo2bb(self.dir_annotations_gt,
self.dir_images_gt,
self.filepath_classes_gt,
bb_type=BBType.GROUND_TRUTH)
# Make all types as GT
[bb.set_bb_type(BBType.GROUND_TRUTH) for bb in ret]
return ret
def load_annotations_det(self):
ret = []
if not self.validate_det_choices():
return ret, False
if self.rad_det_format_coco_json.isChecked():
ret = converter.coco2bb(self.dir_dets, bb_type=BBType.DETECTED)
elif self.rad_det_ci_format_text_yolo_rel.isChecked(
) or self.rad_det_cn_format_text_yolo_rel.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.YOLO,
type_coordinates=CoordinatesType.RELATIVE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_cn_format_text_xyx2y2_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYX2Y2,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xywh_abs.isChecked(
) or self.rad_det_cn_format_text_xywh_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
# Verify if for the selected format, detections were found
if len(ret) == 0:
self.show_popup(
'No file was found for the selected detection format in the annotations directory.',
'No file was found',
buttons=QMessageBox.Ok,
icon=QMessageBox.Information)
return ret, False
# If detection requires class_id, replace the detection names (integers) by a class from the txt file
if self.rad_det_ci_format_text_yolo_rel.isChecked(
) or self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_ci_format_text_xywh_abs.isChecked():
ret = general_utils.replace_id_with_classes(
ret, self.filepath_classes_det)
return ret, True
def test_toy_example_dets_compatibility():
# Checks if all different formats in the toyexample represent the same coordinates
dir_img_dir = 'toyexample/images'
filepath_classes_det = 'toyexample/voc.names'
dir_dets_classid_abs_xywh = 'toyexample/dets_classid_abs_xywh'
dets_classid_abs_xywh = converter.text2bb(dir_dets_classid_abs_xywh,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.ABSOLUTE)
dets_classid_abs_xywh = general_utils.replace_id_with_classes(dets_classid_abs_xywh,
filepath_classes_det)
dets_classid_abs_xywh.sort(key=lambda x: str(x), reverse=True)
dir_dets_classid_abs_xyx2y2 = 'toyexample/dets_classid_abs_xyx2y2'
dets_classid_abs_xyx2y2 = converter.text2bb(dir_dets_classid_abs_xyx2y2,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYX2Y2,
type_coordinates=CoordinatesType.ABSOLUTE)
dets_classid_abs_xyx2y2 = general_utils.replace_id_with_classes(dets_classid_abs_xyx2y2,
filepath_classes_det)
dets_classid_abs_xyx2y2.sort(key=lambda x: str(x), reverse=True)
dir_dets_classid_rel_xcycwh = 'toyexample/dets_classid_rel_xcycwh'
dets_classid_rel_xcycwh = converter.text2bb(dir_dets_classid_rel_xcycwh,
bb_type=BBType.DETECTED,
bb_format=BBFormat.YOLO,
type_coordinates=CoordinatesType.RELATIVE,
img_dir=dir_img_dir)
dets_classid_rel_xcycwh = general_utils.replace_id_with_classes(dets_classid_rel_xcycwh,
filepath_classes_det)
dets_classid_rel_xcycwh.sort(key=lambda x: str(x), reverse=True)
dir_dets_classname_abs_xywh = 'toyexample/dets_classname_abs_xywh'
dets_classname_abs_xywh = converter.text2bb(dir_dets_classname_abs_xywh,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.ABSOLUTE)
dets_classname_abs_xywh.sort(key=lambda x: str(x), reverse=True)
dir_dets_classname_abs_xyx2y2 = 'toyexample/dets_classname_abs_xyx2y2'
dets_classname_abs_xyx2y2 = converter.text2bb(dir_dets_classname_abs_xyx2y2,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYX2Y2,
type_coordinates=CoordinatesType.ABSOLUTE)
dets_classname_abs_xyx2y2.sort(key=lambda x: str(x), reverse=True)
dir_dets_classname_rel_xcycwh = 'toyexample/dets_classname_rel_xcycwh'
dets_classname_rel_xcycwh = converter.text2bb(dir_dets_classname_rel_xcycwh,
bb_type=BBType.DETECTED,
bb_format=BBFormat.YOLO,
type_coordinates=CoordinatesType.RELATIVE,
img_dir=dir_img_dir)
dets_classname_rel_xcycwh.sort(key=lambda x: str(x), reverse=True)
dir_dets_coco_format = 'toyexample/dets_coco_format'
dets_coco_format = converter.coco2bb(dir_dets_coco_format, bb_type=BBType.DETECTED)
dets_coco_format.sort(key=lambda x: str(x), reverse=True)
for a, b, c, d, e, f, g in zip(dets_classid_abs_xywh, dets_classid_abs_xyx2y2,
dets_classid_rel_xcycwh, dets_classname_abs_xywh,
dets_classname_abs_xyx2y2, dets_classname_rel_xcycwh,
dets_coco_format):
assert a == b == c == d == e == f == g
def load_annotations_det(self):
ret = []
# If relative format was required
if self.rad_det_ci_format_text_xywh_rel.isChecked(
) or self.rad_det_cn_format_text_xywh_rel.isChecked():
# Verify if directory with images was provided
if self.dir_images_gt is None or not os.path.isdir(self.dir_images_gt):
self.show_popup(
f'For the selected annotation type, it is necessary to inform a directory with the dataset images.\nDirectory is empty or does not have valid images.',
'Invalid image directory',
buttons=QMessageBox.Ok,
icon=QMessageBox.Information)
return ret, False
if self.rad_det_format_coco_json.isChecked():
ret = converter.coco2bb(self.dir_dets, bb_type=BBType.DETECTED)
elif self.rad_det_ci_format_text_xywh_rel.isChecked(
) or self.rad_det_cn_format_text_xywh_rel.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.RELATIVE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_cn_format_text_xyx2y2_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYX2Y2,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
elif self.rad_det_ci_format_text_xywh_abs.isChecked(
) or self.rad_det_cn_format_text_xywh_abs.isChecked():
ret = converter.text2bb(self.dir_dets,
bb_type=BBType.DETECTED,
bb_format=BBFormat.XYWH,
type_coordinates=CoordinatesType.ABSOLUTE,
img_dir=self.dir_images_gt)
# if its format is in a format that requires class_id, replace the class_id by the class name
if self.rad_det_ci_format_text_xywh_rel.isChecked(
) or self.rad_det_ci_format_text_xyx2y2_abs.isChecked(
) or self.rad_det_ci_format_text_xywh_abs.isChecked():
if self.filepath_classes_det is None or os.path.isfile(
self.filepath_classes_det) is False or len(
general_utils.get_files_dir(
self.dir_images_gt,
extensions=['jpg', 'jpge', 'png', 'bmp', 'tiff', 'tif'])) == 0:
self.show_popup(
f'For the selected annotation type, it is necessary to inform a directory with the dataset images.\nDirectory is empty or does not have valid images.',
'Invalid image directory',
buttons=QMessageBox.Ok,
icon=QMessageBox.Information)
return ret, False
ret = self.replace_id_with_classes(ret, self.filepath_classes_det)
if len(ret) == 0:
self.show_popup(
f'No files was found in the selected directory for the selected annotation format.\nDirectory is empty or does not have valid annotation files.',
'Invalid directory',
buttons=QMessageBox.Ok,
icon=QMessageBox.Information)
return ret, False
return ret, True
plt.ylabel('classes')
else:
plt.bar(dict_bbs_per_class.keys(), dict_bbs_per_class.values())
plt.xlabel('classes')
plt.ylabel('amount of bounding boxes')
plt.xticks(rotation=rotation)
title = f'Distribution of bounding boxes per class {extra_title}'
plt.title(title)
if show:
plt.tick_params(axis='x', labelsize=10) # Set the x-axis label size
plt.show(block=True)
return plt
# Get annotations (ground truth and detections)
gt_bbs = converter.vocpascal2bb(dir_gts)
det_bbs = converter.text2bb(dir_dets, bb_type=BBType.DETECTED, bb_format=BBFormat.XYWH,type_coordinates=CoordinatesType.ABSOLUTE, img_dir=dir_imgs)
# Leave only the annotations of cats
gt_bbs = [bb for bb in gt_bbs if bb.get_class_id() == 'cat']
det_bbs = [bb for bb in det_bbs if bb.get_class_id() == 'cat']
# Uncomment to plot the distribution bounding boxes per classes
# dict_gt = BoundingBox.get_amount_bounding_box_all_classes(gt_bbs, reverse=False)
# plot_bb_per_classes(dict_gt, horizontally=True, rotation=0, show=True, extra_title=' (groundtruths)')
# clases_gt = [b.get_class_id() for b in gt_bbs]
# dict_det = BoundingBox.get_amount_bounding_box_all_classes(det_bbs, reverse=True)
# general_utils.plot_bb_per_classes(dict_det, horizontally=False, rotation=80, show=True, extra_title=' (detections)')
#############################################################
# EVALUATE WITH COCO METRICS
#############################################################
