def process_file(self, filename_in, filename_out,draw_spline=True):
if not os.path.isfile(filename_in):
return []
image = cv2.imread(filename_in)
image = tools_image.rgb2bgr(image)
if image is None:
return []
if draw_spline==False:
boxes_yxyx, scores, classes = self.process_image(image)
markup = tools_YOLO.get_markup(filename_in, boxes_yxyx, scores, classes)
tools_YOLO.draw_and_save(filename_out, image, boxes_yxyx, scores, classes,self.colors, self.class_names)
else:
r = self.model.detect([image], verbose=0)[0]
boxes_yxyx, scores, classes,masks = r['rois'], r['scores'], r['class_ids'],r['masks']
class_ID = tools_IO.smart_index(self.class_names,'person')[0]
msk = (scores > self.obj_threshold).tolist()
#msk = msk and (classes == class_ID)
msk = numpy.array(msk)
boxes_yxyx, scores, classes, masks = boxes_yxyx[msk], scores[msk], classes[msk], masks[:,:,msk]
markup = tools_YOLO.get_markup(filename_in, boxes_yxyx, scores, classes)
detector_Mask_RCNN_core.display_instances(tools_image.desaturate(image), boxes_yxyx, masks, classes, self.class_names,filename_out,scores,self.colors)
return markup
def process_file(self, filename_in, filename_out):
if not os.path.isfile(filename_in):
return []
image = cv2.imread(filename_in)
if image is None:
return []
boxes_yxyx, classes, scores = self.process_image(image)
tools_YOLO.draw_and_save(filename_out, image, boxes_yxyx, scores,
classes, self.colors, self.class_names)
markup = tools_YOLO.get_markup(filename_in, boxes_yxyx, scores,
classes)
return markup
def process_folder_negatives(self,
path_input,
path_out,
list_of_masks='*.png,*.jpg',
limit=1000000,
confidence=0.80):
tools_IO.remove_files(path_out)
local_filenames = tools_IO.get_filenames(path_input,
list_of_masks)[:limit]
local_filenames = numpy.sort(local_filenames)
for local_filename in local_filenames:
image = cv2.imread(path_input + local_filename)
if image is None: return []
boxes_yxyx, classes, scores = self.process_image(image)
if len(scores) > 0 and scores[0] >= confidence:
filename_out = path_out + '%02d_' % int(
100 * scores[0]) + local_filename
tools_YOLO.draw_and_save(filename_out, image, boxes_yxyx,
scores, classes, self.colors,
self.class_names)
return
def draw_and_save(filename_out, image, boxes_yxyx, scores, classes, colors,
class_names):
return tools_YOLO.draw_and_save(filename_out, image, boxes_yxyx, scores,
classes, colors, class_names)