def predict(self, image, display_image):
"""Object detection for flowchart and generate nodes for shapes
and connectors."""
# Image preparation
image = Preprocessor.apply_unsharp_masking(image)
image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
# Format input image
X, ratio = ImageTools.get_format_img_size(image, self.config)
X = np.transpose(X, (0, 2, 3, 1))
# get the feature maps and output from the RPN
[Y1, Y2, F] = self.model_rpn.predict(X)
# Instance a ROI Heper
roi_helper = ROIHelpers(self.config,
overlap_thresh=self.overlap_thresh_1)
R = roi_helper.convert_rpn_to_roi(Y1, Y2)
# convert from (x1,y1,x2,y2) to (x,y,w,h)
R[:, 2] -= R[:, 0]
R[:, 3] -= R[:, 1]
# Apply the spatial pyramid pooling to the proposed regions
bboxes, probs = self.__apply_spatial_pyramid_pooling(R, F)
img, all_dets = self.__generate_final_image(bboxes, probs, image,
roi_helper, ratio)
if (display_image):
cv2.imshow('test', cv2.resize(img, (0, 0), fx=0.4, fy=0.4))
cv2.waitKey(0)
cv2.destroyAllWindows()
return self.generate_nodes(all_dets)
def predict_and_save(self, image, image_name, folder_name):
"""Perform object detection, in this case elements of flowchart and
draw bounding boxes and image and save the same."""
# Image preparation
image = Preprocessor.apply_unsharp_masking(image)
st = time.time() # start time
# Format input image
X, ratio = ImageTools.get_format_img_size(image, self.config)
X = np.transpose(X, (0, 2, 3, 1))
# get the feature maps and output from the RPN
[Y1, Y2, F] = self.model_rpn.predict(X)
# Instance a ROI Heper
roi_helper = ROIHelpers(self.config,
overlap_thresh=self.overlap_thresh_1)
R = roi_helper.convert_rpn_to_roi(Y1, Y2)
# convert from (x1,y1,x2,y2) to (x,y,w,h)
R[:, 2] -= R[:, 0]
R[:, 3] -= R[:, 1]
# Apply the spatial pyramid pooling to the proposed regions
bboxes, probs = self.__apply_spatial_pyramid_pooling(R, F)
img, _ = self.__generate_final_image(bboxes, probs, image, roi_helper,
ratio)
print('Elapsed time = {}'.format(time.time() - st))
# Save image
path = self.results_path + "/" + folder_name
if (os.path.isdir(path) == False):
os.mkdir(path)
cv2.imwrite(path + "/" + image_name, img)
print("Image {}, save in {}".format(image_name, path))
