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bodypix.py
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bodypix.py
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# Copyright 2019 Google LLC
#
# 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
#
# https://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,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import time
import svgwrite
import re
import PIL
import argparse
from functools import partial
from collections import deque
import numpy as np
import scipy.ndimage
import scipy.misc
from PIL import Image
import gstreamer
from pose_engine import PoseEngine, EDGES, BODYPIX_PARTS
# Color mapping for bodyparts
RED_BODYPARTS = [k for k,v in BODYPIX_PARTS.items() if "right" in v]
GREEN_BODYPARTS = [k for k,v in BODYPIX_PARTS.items() if "hand" in v or "torso" in v]
BLUE_BODYPARTS = [k for k,v in BODYPIX_PARTS.items() if "leg" in v or "arm" in v or "face" in v or "hand" in v]
def shadow_text(dwg, x, y, text, font_size=16):
dwg.add(dwg.text(text, insert=(x + 1, y + 1), fill='black',
font_size=font_size, style='font-family:sans-serif'))
dwg.add(dwg.text(text, insert=(x, y), fill='white',
font_size=font_size, style='font-family:sans-serif'))
def draw_pose(dwg, pose, color='blue', threshold=0.2):
xys = {}
for label, keypoint in pose.keypoints.items():
if keypoint.score < threshold: continue
xys[label] = (int(keypoint.yx[1]), int(keypoint.yx[0]))
dwg.add(dwg.circle(center=(int(keypoint.yx[1]), int(keypoint.yx[0])), r=5,
fill='cyan', stroke=color))
for a, b in EDGES:
if a not in xys or b not in xys: continue
ax, ay = xys[a]
bx, by = xys[b]
dwg.add(dwg.line(start=(ax, ay), end=(bx, by), stroke=color, stroke_width=2))
class Callback:
def __init__(self, engine, anonymize=True, bodyparts=True):
self.engine = engine
self.anonymize = anonymize
self.bodyparts = bodyparts
self.background_image = None
self.last_time = time.monotonic()
self.frames = 0
self.sum_fps = 0
self.sum_process_time = 0
self.sum_inference_time = 0
def __call__(self, image, svg_canvas):
start_time = time.monotonic()
inference_time, poses, heatmap, bodyparts = self.engine.DetectPosesInImage(image)
def clip_heatmap(heatmap, v0, v1):
a = v0 / (v0 - v1);
b = 1.0 / (v1 - v0);
return np.clip(a + b * heatmap, 0.0, 1.0);
# clip heatmap to create a mask
heatmap = clip_heatmap(heatmap, -1.0, 1.0)
if self.bodyparts:
rgb_heatmap = np.dstack([
heatmap*(np.sum(bodyparts[:,:,RED_BODYPARTS], axis=2)-0.5)*100,
heatmap*(np.sum(bodyparts[:,:,GREEN_BODYPARTS], axis=2)-0.5)*100,
heatmap*(np.sum(bodyparts[:,:,BLUE_BODYPARTS], axis=2)-0.5)*100,
])
else:
rgb_heatmap = np.dstack([heatmap[:,:]*100]*3)
rgb_heatmap[:,:,1:] = 0 # make it red
rgb_heatmap= 155*np.clip(rgb_heatmap, 0, 1)
rescale_factor = [
image.shape[0]/heatmap.shape[0],
image.shape[1]/heatmap.shape[1],
1]
rgb_heatmap = scipy.ndimage.zoom(rgb_heatmap, rescale_factor, order=0)
if self.anonymize:
if self.background_image is None:
self.background_image = np.float32(np.zeros_like(image))
# Estimate instantaneous background
mask = np.clip(np.sum(rgb_heatmap, axis=2), 0, 1)[:,:,np.newaxis]
background_estimate = (self.background_image*mask+ image*(1.0-mask))
# Mix into continuous estimate with decay
ratio = 1/max(1,self.frames/2.0)
self.background_image = self.background_image*(1.0-ratio) + ratio*background_estimate
else:
self.background_image = image
output_image = self.background_image + rgb_heatmap
int_img = np.uint8(np.clip(output_image,0,255))
end_time = time.monotonic()
self.frames += 1
self.sum_fps += 1.0 / (end_time - self.last_time)
self.sum_process_time += 1000 * (end_time - start_time) - inference_time
self.sum_inference_time += inference_time
self.last_time = end_time
text_line = 'PoseNet: %.1fms Frame IO: %.2fms TrueFPS: %.2f Nposes %d' % (
self.sum_inference_time / self.frames,
self.sum_process_time / self.frames,
self.sum_fps / self.frames,
len(poses)
)
shadow_text(svg_canvas, 10, 20, text_line)
for pose in poses:
draw_pose(svg_canvas, pose)
print(text_line)
return int_img
def main():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--mirror', help='flip video horizontally', action='store_true')
parser.add_argument('--model', help='.tflite model path.', required=False)
parser.add_argument('--width', help='Source width', default='640')
parser.add_argument('--height', help='Source height', default='480')
parser.add_argument('--videosrc', help='Which video source to use', default='/dev/video0')
parser.add_argument('--anonymize', dest='anonymize', action='store_true', help='Use anonymizer mode [--noanonymize]')
parser.add_argument('--noanonymize', dest='anonymize', action='store_false', help=argparse.SUPPRESS)
parser.set_defaults(anonymize=False)
parser.add_argument('--bodyparts', dest='bodyparts', action='store_true', help='Color by bodyparts [--nobodyparts]')
parser.add_argument('--nobodyparts', dest='bodyparts', action='store_false', help=argparse.SUPPRESS)
parser.set_defaults(bodyparts=True)
parser.add_argument('--h264', help='Use video/x-h264 input', action='store_true')
parser.add_argument('--jpeg', help='Use video/jpeg input', action='store_true')
args = parser.parse_args()
if args.h264 and args.jpeg:
print('Error: both mutually exclusive options h264 and jpeg set')
sys.exit(1)
default_model = 'models/bodypix_mobilenet_v1_075_640_480_16_quant_decoder_edgetpu.tflite'
model = args.model if args.model else default_model
print('Model: {}'.format(model))
engine = PoseEngine(model)
inference_size = (engine.image_width, engine.image_height)
print('Inference size: {}'.format(inference_size))
src_size = (int(args.width), int(args.height))
if args.videosrc.startswith('/dev/video'):
print('Source size: {}'.format(src_size))
gstreamer.run_pipeline(Callback(engine,
anonymize=args.anonymize,
bodyparts=args.bodyparts),
src_size, inference_size,
mirror=args.mirror,
videosrc=args.videosrc,
h264=args.h264,
jpeg=args.jpeg)
if __name__ == '__main__':
main()