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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
import logging
from ... import c_lib_wrap as C
import cv2
[docs]def vis_detection(im_data,
det_result,
labels=[],
score_threshold=0.0,
line_size=1,
font_size=0.5):
"""Show the visualized results for detection models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param det_result: the result produced by model
:param labels: (list of str) the visualized result will show the bounding box contain class label
:param score_threshold: (float) score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
:param line_size: (float) line_size line size for bounding boxes
:param font_size: (float) font_size font size for text
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_detection(im_data, det_result, labels, score_threshold,
line_size, font_size)
[docs]def vis_keypoint_detection(im_data, keypoint_det_result, conf_threshold=0.5):
"""Show the visualized results for keypoint detection models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param keypoint_det_result: the result produced by model
:param conf_threshold: (float) conf_threshold threshold for result scores, the bounding box will not be shown if the score is less than conf_threshold
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.Visualize.vis_keypoint_detection(
im_data, keypoint_det_result, conf_threshold)
[docs]def vis_face_detection(im_data, face_det_result, line_size=1, font_size=0.5):
"""Show the visualized results for face detection models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param face_det_result: the result produced by model
:param line_size: (float) line_size line size for bounding boxes
:param font_size: (float) font_size font size for text
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_face_detection(im_data, face_det_result, line_size,
font_size)
[docs]def vis_face_alignment(im_data, face_align_result, line_size=1):
"""Show the visualized results for face alignment models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param face_align_result: the result produced by model
:param line_size: (float)line_size line size for circle point
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_face_alignment(im_data, face_align_result, line_size)
[docs]def vis_segmentation(im_data, seg_result, weight=0.5):
"""Show the visualized results for segmentation models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param seg_result: the result produced by model
:param weight: (float)transparent weight of visualized result image
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_segmentation(im_data, seg_result, weight)
def vis_matting_alpha(im_data,
matting_result,
remove_small_connected_area=False):
logging.warning(
"DEPRECATED: fastdeploy.vision.vis_matting_alpha is deprecated, please use fastdeploy.vision.vis_matting function instead."
)
return C.vision.vis_matting(im_data, matting_result,
remove_small_connected_area)
[docs]def vis_matting(im_data,
matting_result,
transparent_background=False,
transparent_threshold=0.99,
remove_small_connected_area=False):
"""Show the visualized results for matting models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param matting_result: the result produced by model
:param transparent_background: whether visulizing matting result with transparent background
:param transparent_threshold: since the alpha value in MattringResult is a float between [0, 1], transparent_threshold is used to filter background pixel
:param remove_small_connected_area: (bool) if remove_small_connected_area==True, the visualized result will not include the small connected areas
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_matting(im_data, matting_result,
transparent_background, transparent_threshold,
remove_small_connected_area)
def swap_background_matting(im_data,
background,
result,
remove_small_connected_area=False):
logging.warning(
"DEPRECATED: fastdeploy.vision.swap_background_matting is deprecated, please use fastdeploy.vision.swap_background function instead."
)
assert isinstance(
result,
C.vision.MattingResult), "The result must be MattingResult type"
return C.vision.Visualize.swap_background_matting(
im_data, background, result, remove_small_connected_area)
def swap_background_segmentation(im_data, background, background_label,
result):
logging.warning(
"DEPRECATED: fastdeploy.vision.swap_background_segmentation is deprecated, please use fastdeploy.vision.swap_background function instead."
)
assert isinstance(
result, C.vision.
SegmentationResult), "The result must be SegmentaitonResult type"
return C.vision.Visualize.swap_background_segmentation(
im_data, background, background_label, result)
def swap_background(im_data,
background,
result,
remove_small_connected_area=False,
background_label=0):
"""Swap the image background with MattingResult or SegmentationResult
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param background: (numpy.ndarray)The background image data, 3-D array with layout HWC, BGR format
:param result: The result produced by model, MattingResult or SegmentationResult
:param remove_small_connected_area: (bool) If remove_small_connected_area==True, the visualized result will not include the small connected areas
:param background_label: (int)The background label number in SegmentationResult
:return: (numpy.ndarray) image with visualized results
"""
if isinstance(result, C.vision.MattingResult):
return C.vision.swap_background(im_data, background, result,
remove_small_connected_area)
elif isinstance(result, C.vision.SegmentationResult):
return C.vision.swap_background(im_data, background, result,
background_label)
else:
raise Exception(
"Only support result type of MattingResult or SegmentationResult, but now the data type is {}.".
format(type(result)))
[docs]def vis_ppocr(im_data, det_result):
"""Show the visualized results for ocr models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param det_result: the result produced by model
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_ppocr(im_data, det_result)
def vis_mot(im_data, mot_result, score_threshold=0.0, records=None):
return C.vision.vis_mot(im_data, mot_result, score_threshold, records)
def vis_headpose(im_data, headpose_result, size=50, line_size=1):
return C.vision.vis_headpose(im_data, headpose_result, size, line_size)