def __init__(self,
model=DEFAULT_MODEL,
device='CPU',
model_input_height=256,
upsample_ratio=4,
color_palette="openpose"):
self.stride = 8
self.inference_engine = InferenceEngine(model, device, self.stride)
self.model_input_height = model_input_height
self.upsample_ratio = upsample_ratio
self.color_palette = color_palette
class HumanPose:
def __init__(self,
model=DEFAULT_MODEL,
device='CPU',
model_input_height=256,
upsample_ratio=4,
color_palette="openpose"):
self.stride = 8
self.inference_engine = InferenceEngine(model, device, self.stride)
self.model_input_height = model_input_height
self.upsample_ratio = upsample_ratio
self.color_palette = color_palette
def eval(self, frame):
input_scale = self.model_input_height / frame.shape[0]
scaled_img = cv2.resize(frame,
dsize=None,
fx=input_scale,
fy=input_scale)
# Inference
inference_result = self.inference_engine.infer(scaled_img)
# Postprocessing (grouping)
poses_2d = parse_poses(inference_result, input_scale, self.stride,
self.upsample_ratio) #, threshold)
return poses_2d
def draw(self, frame, poses_2d, draw_fps=False):
draw_poses(frame, poses_2d, color_palette=self.color_palette)
def __init__(self, parent, capture, height, width, counter_label, motion, fps=24):
wx.Panel.__init__(self, parent)
assert motion in ('jumpingjack','situp','squat')
# set model parameter
model = "human-pose-estimation-0001.xml"
device = "CPU"
self.base_height = 256
self.inference_engine = InferenceEngine(model, device,8)
# set parameter for count action
self.motion = motion
self.up=False
self.count=0
# label for update counter
self.counter_label = counter_label
# limit size of screen
self.width = width
self.height = height
# set panel size and position
self.SetSize(width,height)
self.SetPosition(wx.Point(50,10))
# capture rgb frame
self.capture = capture
ret, rgb = self.capture.read()
rgb = cv2.cvtColor(rgb, cv2.COLOR_BGR2RGB)
rgb = cv2.resize(rgb, (self.width, self.height))
self.bmp = wx.Bitmap.FromBuffer(self.width, self.height, rgb)
self.timer = wx.Timer(self)
self.timer.Start(1000/fps+1)
self.Bind(wx.EVT_PAINT, self.OnPaint)
self.Bind(wx.EVT_TIMER, self.NextFrame)
default=-1,
help='Optional. Camera focal length.')
args.add_argument('--no_show',
help='Optional. Do not display output.',
action='store_true')
args.add_argument("-u",
"--utilization_monitors",
default='',
type=str,
help="Optional. List of monitors to show initially.")
args = parser.parse_args()
cap = open_images_capture(args.input, args.loop)
stride = 8
inference_engine = InferenceEngine(args.model, args.device, stride)
canvas_3d = np.zeros((720, 1280, 3), dtype=np.uint8)
plotter = Plotter3d(canvas_3d.shape[:2])
canvas_3d_window_name = 'Canvas 3D'
if not args.no_show:
cv2.namedWindow(canvas_3d_window_name)
cv2.setMouseCallback(canvas_3d_window_name, Plotter3d.mouse_callback)
file_path = args.extrinsics_path
if file_path is None:
file_path = Path(__file__).parent / 'data/extrinsics.json'
with open(file_path, 'r') as f:
extrinsics = json.load(f)
R = np.array(extrinsics['R'], dtype=np.float32)
t = np.array(extrinsics['t'], dtype=np.float32)
class ShowCamCapture(wx.Panel):
def __init__(self, parent, capture, height, width, counter_label, motion, fps=24):
wx.Panel.__init__(self, parent)
assert motion in ('jumpingjack','situp','squat')
# set model parameter
model = "human-pose-estimation-0001.xml"
device = "CPU"
self.base_height = 256
self.inference_engine = InferenceEngine(model, device,8)
# set parameter for count action
self.motion = motion
self.up=False
self.count=0
# label for update counter
self.counter_label = counter_label
# limit size of screen
self.width = width
self.height = height
# set panel size and position
self.SetSize(width,height)
self.SetPosition(wx.Point(50,10))
# capture rgb frame
self.capture = capture
ret, rgb = self.capture.read()
rgb = cv2.cvtColor(rgb, cv2.COLOR_BGR2RGB)
rgb = cv2.resize(rgb, (self.width, self.height))
self.bmp = wx.Bitmap.FromBuffer(self.width, self.height, rgb)
self.timer = wx.Timer(self)
self.timer.Start(1000/fps+1)
self.Bind(wx.EVT_PAINT, self.OnPaint)
self.Bind(wx.EVT_TIMER, self.NextFrame)
def OnPaint(self, evt):
dc = wx.BufferedPaintDC(self)
dc.DrawBitmap(self.bmp, 0, 0)
def NextFrame(self, event):
ret, rgb = self.capture.read()
self.counter_label.SetLabel("Times: " + str(self.count))
if ret:
input_scale = self.base_height / rgb.shape[0]
scaled_img = cv2.resize(rgb, dsize=None, fx=input_scale, fy=input_scale)
inference_result = self.inference_engine.infer(scaled_img)
poses_2d = parse_poses(inference_result, input_scale, 8, -1, True)
draw_poses(rgb, poses_2d)
if self.motion=="jumpingjack":
self.up,self.count = count_jumpup(poses_2d,self.up,self.count)
elif self.motion=="situp":
self.up,self.count = count_situp(poses_2d,self.up,self.count)
elif self.motion=="squat":
self.up,self.count = count_squat(poses_2d,self.up,self.count)
rgb = cv2.cvtColor(rgb, cv2.COLOR_BGR2RGB)
self.bmp.CopyFromBuffer(rgb)
self.Refresh()
else:
self.timer.Stop()