def test_workflow_exception_when_tensor_flow_inference_call_fails(self):
self.mock_tf_call_service.run.side_effect = WorkflowException()
self.workflow = WorkFlow(self.graph, self.chunk_image,
self.mock_tf_call_service,
self.mock_apply_coordinate_correction, None,
None, None, None, self.provider)
self.workflow.run()
self.workflow.apply_coordinate_correction.run.assert_not_called()
def test_workflow_exception_when_chunk_fails(self):
self.mock_chunk_image.run.side_effect = WorkflowException()
self.tf_call_service = mock.MagicMock(TfCall())
self.workflow = WorkFlow(self.graph, self.mock_chunk_image,
self.tf_call_service, None, None, None, None,
None, self.provider)
self.workflow.run()
self.workflow.tf_call_service.run.assert_not_called()
def test_workflow_exception_when_post_processing_fails(self):
self.mock_tf_call_service.run.return_value = \
{(1536, 8192):
[Rect(562, 954, 665, 111, 0.3364628255367279)]}
self.mock_post_processing.run.side_effect = WorkflowException()
self.workflow = WorkFlow(
self.graph, self.chunk_image, self.mock_tf_call_service,
self.apply_coordinate_correction, self.filter_merge_boxes,
self.mock_label_service, self.mock_coordinate_storage,
self.mock_post_processing, self.provider)
self.workflow.run()
self.workflow.provider.acknowledge.assert_not_called()
def run(self):
try:
img = cv2.imdecode(self.byte_array, cv2.IMREAD_UNCHANGED)
start_x, start_y = 0, 0
end_y, end_x, _ = img.shape
positions = self.get_pano_positions(
start_x, start_y, end_y, end_x,
TFCONST.config('OOS_STRIDE_INFO')['height'],
TFCONST.config('OOS_STRIDE_INFO')['width'],
TFCONST.config('OOS_STRIDE_INFO')['h_stride'],
TFCONST.config('OOS_STRIDE_INFO')['w_stride'])
except Exception as e:
raise WorkflowException(
'Image Chunking Exception in ' +
'line {0} for container {1} and url {2}'.format(
sys.exc_info()[2].tb_lineno,
self.pano_upload_event.container_name,
self.pano_upload_event.url), e)
return positions, img
def run(self):
try:
all_rects = []
for position, rects in self.positions_rect_dict.items():
i, j = position
for rect in rects:
rect.transform(self.resize_factor, j, i)
all_rects.append(rect)
logDebug(
"rects after coordinate correction {0} ".format(all_rects))
except Exception as e:
raise WorkflowException(
'Coordinate Correction Exception in ' +
'line {0} for container {1} and url {2}'.format(
sys.exc_info()[2].tb_lineno,
self.pano_upload_event.container_name,
self.pano_upload_event.url), e)
return all_rects
def run(self):
''' This method filters and merge the boxes '''
try:
final_indices = {}
final_rects = sorted(self.rects,
key=lambda r: r.width * r.height,
reverse=True)
for i in range(len(final_rects)):
if i in final_indices:
curr_root = final_indices[i]
else:
curr_root = i
rect = final_rects[curr_root]
for j in range(i + 1, len(final_rects)):
if j in final_indices:
other = final_rects[final_indices[j]]
else:
other = final_rects[j]
cov = other.cov(rect)
if cov > TFCONST.config('OOS_ARGS')['iou_threshold']:
final_indices[j] = curr_root
final_rects = list(
set([
final_rects[i] if i not in final_indices else
final_rects[final_indices[i]]
for i in range(len(final_rects))
]))
except Exception as e:
raise WorkflowException(
'Filter Merge Boxes Exception in ' +
'line {0} for container {1} and url {2}'.format(
sys.exc_info()[2].tb_lineno,
self.pano_upload_event.container_name,
self.pano_upload_event.url), e)
return final_rects
def run(self):
try:
oos_coords_input = reformat_oos_coords_to_x_y_axis(self.oos_coords)
label_coords_input = reformat_label_coords_to_x_y_axis(
self.label_coords)
logDebug('oos coordinates before pre processing = {0} {1}'.format(
oos_coords_input, self._add_container_n_url_name()))
logDebug(
'label coordinates before pre processing = {0} {1}'.format(
label_coords_input, self._add_container_n_url_name()))
oos_rects = read_boxes(oos_coords_input)
label_rects = read_boxes(label_coords_input)
oos_rects = [r for r in oos_rects if r.score > self.min_conf]
oos_rects = filter_boxes_by_size(oos_rects,
min_w=150,
min_h=80,
max_asp_ratio=12)
label_rects = filter_boxes_by_size(label_rects, min_w=40, min_h=20)
if len(label_rects) == 0:
return {
'oos_coordinates': format_coords_output(oos_rects),
'label_coordinates': None,
'detection_boxes':
filter_oos_by_labels(oos_rects, label_rects)
}
shelf_rects = read_boxes(extract_shelves(label_rects))
logInfo('no of oos before processing with shelves {0} {1}'.format(
len(oos_rects), self._add_container_n_url_name()))
oos_rects, removed_rects = filter_boxes_by_shelves(
oos_rects, shelf_rects)
logInfo('no of oos within shelf = {0} {1}'.format(
len(oos_rects), self._add_container_n_url_name()))
logInfo('no of labels = {0} {1}'.format(
len(label_rects), self._add_container_n_url_name()))
# add labels that is part of oos regions.
detection_boxes = filter_oos_by_labels(oos_rects, label_rects)
logInfo('no of labels within oos region = {0} {1} '.format(
len(label_rects), self._add_container_n_url_name()))
# This can removed - Added for debugging.
oos_coordinates = format_coords_output(
detection_boxes.oos_coordinates)
label_coordinates = format_coords_output(
detection_boxes.label_coordinates)
logDebug('final shelf coordinates = {0} {1}'.format(
shelf_rects, self._add_container_n_url_name()))
logDebug('final oos coordinates = {0} {1}'.format(
oos_coordinates, self._add_container_n_url_name()))
logDebug('final label coordinates = {0} {1} '.format(
label_coordinates, self._add_container_n_url_name()))
except Exception as e:
raise WorkflowException(
'Post Process Exception in ' +
'line {0} for container {1} and url {2}'.format(
sys.exc_info()[2].tb_lineno,
self.pano_upload_event.container_name,
self.pano_upload_event.url), e)
return {
'detection_boxes': detection_boxes,
'oos_coordinates': oos_coordinates,
'label_coordinates': label_coordinates
}