def doPoseAdjustment(imageToProcess,
folder_path,
webcam_number=1,
nn_model="BODY_25",
pose_model="SL",
fitted=True):
if fitted:
width, height = get_curr_screen_geometry()
else:
width, height = 640, 480
nn_mapping, new_mapping, new_pairs = getPoseParameters(
nn_model, pose_model)
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = openpose_path + "models/"
try:
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
datum = op.Datum()
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
pose_keypoints = datum.poseKeypoints
try:
pose_keypoints = pose_keypoints[:, :, :2]
except:
pose_keypoints = np.zeros([1, len(new_mapping), 2])
pose_keypoints = selectJoints(pose_keypoints, nn_mapping, new_mapping)
pose_keypoints = organizeBiggestPerson(pose_keypoints)
pose_keypoints = pose_keypoints[0]
for i in range(len(pose_keypoints)):
if 0 in pose_keypoints[i]:
pose_keypoints[i,
0], pose_keypoints[i, 1] = imageToProcess.shape[
0] / 2, imageToProcess.shape[1] / 2
joint_n = 0
k = 1
while True:
image = np.copy(imageToProcess)
img_out = poseDATAtoFrame(image,
pose_keypoints,
0,
new_mapping,
new_pairs,
thickness=1,
color=-1)
for i in range(len(pose_keypoints)):
A = tuple(pose_keypoints[i].astype(int))
if (i == joint_n):
cv2.circle(img_out, (A[0], A[1]), 1, (255, 255, 255), -1)
else:
cv2.circle(img_out, (A[0], A[1]), 1, (0, 0, 0), -1)
img_processed = np.copy(img_out)
img_out = cv2.copyMakeBorder(img_out,
50,
0,
0,
0,
cv2.BORDER_CONSTANT,
value=[0, 0, 0])
cv2.putText(img_out,
"{}".format(new_mapping[joint_n]), (200, 30),
cv2.FONT_HERSHEY_COMPLEX,
.8, (255, 255, 255),
2,
lineType=cv2.LINE_AA)
cv2.putText(img_out,
"k: {}".format(k), (450, 30),
cv2.FONT_HERSHEY_COMPLEX,
.8, (255, 255, 255),
2,
lineType=cv2.LINE_AA)
img_out[40:45, 450:450 + k, :] = 255
cv2.namedWindow('OpenPose', cv2.WINDOW_NORMAL)
cv2.resizeWindow('OpenPose', (width, height))
cv2.imshow("OpenPose", img_out)
key = cv2.waitKey(30)
if key == ord('q'):
print("Not saving...")
break
elif key == 81: #left
pose_keypoints[joint_n, 0] -= k
elif key == 82: #up
pose_keypoints[joint_n, 1] -= k
elif key == 83: #right
pose_keypoints[joint_n, 0] += k
elif key == 84: #down
pose_keypoints[joint_n, 1] += k
elif key == 171: #+
k += 1
elif key == 173: #-
if (k > 1):
k -= 1
elif (key == 32): #space
if (joint_n >= pose_keypoints.shape[0] - 1):
joint_n = 0
else:
joint_n += 1
elif (key == 8):
if (joint_n <= 0 - 1):
joint_n = pose_keypoints.shape[0]
else:
joint_n -= 1
elif (key == 13 or key == 141): #enter
print("Saving dimensions")
cv2.destroyAllWindows()
mmppx, mmppy = getMmppInterface(img_processed)
saveCalibrations(img_processed,
pose_keypoints,
new_mapping,
folder_path,
mmppx,
mmppy,
mode="manual")
break
except KeyboardInterrupt:
print("Not saving...")
cv2.destroyAllWindows()
sys.exit(-1)
def realtimePE(webcam_number=1,
video_name="Webcam",
output_name="Webcam",
nn_model="BODY_25",
pose_model="BODY_25",
process_params="B",
save_video=False,
show_video=True,
save_data=False,
fitted=True):
if fitted:
width, height = get_curr_screen_geometry()
else:
width, height = 640, 480
nn_mapping, new_mapping, new_pairs = getPoseParameters(
nn_model, pose_model)
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = openpose_path + "models/"
try:
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
datum = op.Datum()
video_out_path, output_path = setOutputPath(video_name, output_name)
file_metadata = setMetadata(0, new_mapping, new_pairs)
frame_width, frame_height, fps = file_metadata[
"frame_width"], file_metadata["frame_height"], file_metadata["fps"]
cap = cv2.VideoCapture(webcam_number)
if save_data:
writeToDATA(output_path, file_metadata, write_mode='w')
if save_video:
fourcc = cv2.VideoWriter_fourcc(*'X264')
vid_writer = cv2.VideoWriter(video_out_path, fourcc, fps,
(frame_width, frame_height))
if (cap.isOpened() == False):
print("Error opening video stream or file")
while (cap.isOpened):
# Process Image
ret, imageToProcess = cap.read()
if not ret:
break
# Start timer
timer = cv2.getTickCount()
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
pose_keypoints = datum.poseKeypoints
try:
pose_keypoints = pose_keypoints[:, :, :2]
except:
pose_keypoints = np.zeros([1, len(new_mapping), 2])
pose_keypoints = selectJoints(pose_keypoints, nn_mapping,
new_mapping)
if 'B' in process_params:
pose_keypoints = organizeBiggestPerson(pose_keypoints)
pose_keypoints = pose_keypoints[0]
if show_video or save_video or show_frame:
if 'B' in process_params:
img_out = poseDATAtoFrame(imageToProcess,
pose_keypoints,
0,
new_mapping,
new_pairs,
thickness=3,
color=-1)
else:
img_out = poseDATAtoFrame(imageToProcess,
pose_keypoints, [0],
new_mapping,
new_pairs,
thickness=3,
color=-1)
if save_video:
vid_writer.write(img_out)
if save_data:
pose_keypoints = np.round(pose_keypoints).astype(int)
file_data = {'keypoints': pose_keypoints.tolist()}
writeToDATA(output_path, file_data, write_mode='a')
if show_video or show_frame:
# Calculate Frames per second (FPS)
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
# Display FPS on frame
cv2.putText(img_out, "FPS : " + str(int(fps)), (100, 50),
cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
# Display Image
cv2.namedWindow('OpenPose', cv2.WINDOW_NORMAL)
cv2.resizeWindow('OpenPose', (width, height))
cv2.imshow("OpenPose", img_out)
if (cv2.waitKey(25) & 0xFF == ord('q')):
break
except KeyboardInterrupt:
cap.release()
cv2.destroyAllWindows()
sys.exit(-1)
def poseAutomaticAdjustmentInterface(n_mean=5,
enter_folder=True,
webcam_number=1,
nn_model="BODY_25",
pose_model="SL",
fitted=True):
if fitted:
width, height = get_curr_screen_geometry()
else:
width, height = 640, 480
if enter_folder:
folder_path = saveSelectedFolder()
else:
folder_path = repo_path + "Calib/" + "Tmp"
print("Get set...")
time.sleep(10)
print("Started")
nn_mapping, new_mapping, new_pairs = getPoseParameters(
nn_model, pose_model)
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = openpose_path + "models/"
try:
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
cap = cv2.VideoCapture(webcam_number)
if (cap.isOpened() == False):
print("Error opening video stream or file")
keep_running = True
while keep_running:
ret, imageToProcess = cap.read()
frame = np.copy(imageToProcess)
if not ret:
break
datum = op.Datum()
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
pose_keypoints = datum.poseKeypoints
try:
pose_keypoints = pose_keypoints[:, :, :2]
except:
pose_keypoints = np.zeros([1, len(new_mapping), 2])
pose_keypoints = selectJoints(pose_keypoints, nn_mapping,
new_mapping)
pose_keypoints = organizeBiggestPerson(pose_keypoints)
pose_keypoints = pose_keypoints[0]
img_processed = poseDATAtoFrame(imageToProcess,
pose_keypoints,
0,
new_mapping,
new_pairs,
thickness=1,
color=-1)
for i in range(len(pose_keypoints)):
if 0 in pose_keypoints[i]:
print("Wait till all joints are found")
else:
keep_running = False
if not keep_running:
print("Joints found")
except KeyboardInterrupt:
print("Not saving...")
cv2.destroyAllWindows()
sys.exit(-1)
mmppx, mmppy = getMmppAutomatically(frame)
saveCalibrations(img_processed,
pose_keypoints,
new_mapping,
folder_path,
mmppx,
mmppy,
mode="automatic",
show_plot=False)