def msvs_setup_env(env):
batfilename = msvs.get_batch_file()
msvs = get_vs_by_version(version)
if msvs is None:
return
# XXX: I think this is broken. This will silently set a bogus tool instead
# of failing, but there is no other way with the current scons tool
# framework
if batfilename is not None:
vars = ('LIB', 'LIBPATH', 'PATH', 'INCLUDE')
msvs_list = get_installed_visual_studios()
vscommonvarnames = [vs.common_tools_var for vs in msvs_list]
save_ENV = env['ENV']
nenv = normalize_env(env['ENV'],
['COMSPEC'] + vscommonvarnames,
force=True)
try:
output = get_output(batfilename, arch, env=nenv)
finally:
env['ENV'] = save_ENV
vars = parse_output(output, vars)
for k, v in vars.items():
env.PrependENVPath(k, v, delete_existing=1)
def msvs_setup_env(env):
batfilename = msvs.get_batch_file()
msvs = get_vs_by_version(version)
if msvs is None:
return
# XXX: I think this is broken. This will silently set a bogus tool instead
# of failing, but there is no other way with the current scons tool
# framework
if batfilename is not None:
vars = ('LIB', 'LIBPATH', 'PATH', 'INCLUDE')
msvs_list = get_installed_visual_studios()
vscommonvarnames = [vs.common_tools_var for vs in msvs_list]
save_ENV = env['ENV']
nenv = normalize_env(env['ENV'], ['COMSPEC'] + vscommonvarnames,
force=True)
try:
output = get_output(batfilename, arch, env=nenv)
finally:
env['ENV'] = save_ENV
vars = parse_output(output, vars)
for k, v in vars.items():
env.PrependENVPath(k, v, delete_existing=1)
def merge_default_version(env):
version = get_default_version(env)
arch = get_default_arch(env)
msvs = get_vs_by_version(version)
if msvs is None:
return
batfilename = msvs.get_batch_file()
# XXX: I think this is broken. This will silently set a bogus tool instead
# of failing, but there is no other way with the current scons tool
# framework
if batfilename is not None:
vars = ('LIB', 'LIBPATH', 'PATH', 'INCLUDE')
msvs_list = get_installed_visual_studios()
# TODO(1.5):
#vscommonvarnames = [ vs.common_tools_var for vs in msvs_list ]
vscommonvarnames = map(lambda vs: vs.common_tools_var, msvs_list)
nenv = normalize_env(env['ENV'], vscommonvarnames + ['COMSPEC'])
output = get_output(batfilename, arch, env=nenv)
vars = parse_output(output, vars)
for k, v in vars.items():
env.PrependENVPath(k, v, delete_existing=1)
def merge_default_version(env):
version = get_default_version(env)
arch = get_default_arch(env)
msvs = get_vs_by_version(version)
if msvs is None:
return
batfilename = msvs.get_batch_file()
# XXX: I think this is broken. This will silently set a bogus tool instead
# of failing, but there is no other way with the current scons tool
# framework
if batfilename is not None:
vars = ('LIB', 'LIBPATH', 'PATH', 'INCLUDE')
msvs_list = get_installed_visual_studios()
# TODO(1.5):
#vscommonvarnames = [ vs.common_tools_var for vs in msvs_list ]
vscommonvarnames = map(lambda vs: vs.common_tools_var, msvs_list)
nenv = normalize_env(env['ENV'], vscommonvarnames + ['COMSPEC'])
output = get_output(batfilename, arch, env=nenv)
vars = parse_output(output, vars)
for k, v in vars.items():
env.PrependENVPath(k, v, delete_existing=1)
def script_env(script, args=None):
stdout = common.get_output(script, args)
# Stupid batch files do not set return code: we take a look at the
# beginning of the output for an error message instead
olines = stdout.splitlines()
if olines[0].startswith("The specified configuration type is missing"):
raise BatchFileExecutionError("\n".join(olines[:2]))
return common.parse_output(stdout)
def start_detector(args, interpreter, labels, camera_res):
""" Detect max_objs objects from camera frames. """
detected_objects.clear()
try:
cap = cv2.VideoCapture(args.camera_idx)
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
cv2_im = frame
cv2_im_u = cv2.undistort(cv2_im, common.CAMERA_MATRIX,
common.DIST_COEFFS)
cv2_im_u_rgb = cv2.cvtColor(cv2_im_u, cv2.COLOR_BGR2RGB)
pil_im = Image.fromarray(cv2_im_u_rgb)
common.set_input(interpreter, pil_im)
interpreter.invoke()
objs = common.get_output(interpreter,
score_threshold=args.threshold,
labels=labels)
# Reject images with number of detected objects > max_objs.
if len(objs) > args.max_objs:
continue
# Create proto buffer message and add to stack.
for obj in objs:
detected_object = detection_server_pb2.DetectedObject(
label=obj.label,
score=obj.score,
area=obj.area,
centroid=detection_server_pb2.DetectedObject.Centroid(
x=obj.centroid.x, y=obj.centroid.y),
bbox=detection_server_pb2.DetectedObject.BBox(
xmin=obj.bbox.xmin,
ymin=obj.bbox.ymin,
xmax=obj.bbox.xmax,
ymax=obj.bbox.ymax))
detected_objects.appendleft(detected_object)
if args.display:
cv2_im_u = common.annotate_image(objs, camera_res, cv2_im_u)
cv2.imshow('frame', cv2_im_u)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
except cv2.error as e:
print('cv2 error: {e}'.format(e))
finally:
cap.release()
cv2.destroyAllWindows()
return
def main():
if (edgetpu==1):
mdl = model_edgetpu
else:
mdl = model
interpreter, labels =cm.load_model(model_dir,model_edgetpu,lbl,edgetpu)
fps=1
while True:
start_time=time.time()
#----------------Capture Camera Frame-----------------
ret, frame = cap.read()
if not ret:
break
cv2_im = frame
cv2_im = cv2.flip(cv2_im, 0)
cv2_im = cv2.flip(cv2_im, 1)
cv2_im_rgb = cv2.cvtColor(cv2_im, cv2.COLOR_BGR2RGB)
pil_im = Image.fromarray(cv2_im_rgb)
#-------------------Inference---------------------------------
cm.set_input(interpreter, pil_im)
interpreter.invoke()
objs = cm.get_output(interpreter, score_threshold=threshold, top_k=top_k)
#-----------------other------------------------------------
track_object(objs,labels)#tracking <<<<<<<
fps = round(1.0 / (time.time() - start_time),1)
print("*********FPS: ",fps,"************")
#-----------------------------------------------------
cap.release()
cv2.destroyAllWindows()
def main():
if (edgetpu == 1):
mdl = model_edgetpu
else:
mdl = model
interpreter, labels = cm.load_model(model_dir, mdl, lbl, edgetpu)
fps = 1
arr_dur = [0, 0, 0]
#while cap.isOpened():
while True:
start_time = time.time()
#----------------Capture Camera Frame-----------------
start_t0 = time.time()
ret, frame = cap.read()
if not ret:
break
cv2_im = frame
cv2_im = cv2.flip(cv2_im, 0)
cv2_im = cv2.flip(cv2_im, 1)
cv2_im_rgb = cv2.cvtColor(cv2_im, cv2.COLOR_BGR2RGB)
pil_im = Image.fromarray(cv2_im_rgb)
arr_dur[0] = time.time() - start_t0
#cm.time_elapsed(start_t0,"camera capture")
#----------------------------------------------------
#-------------------Inference---------------------------------
start_t1 = time.time()
cm.set_input(interpreter, pil_im)
interpreter.invoke()
objs = cm.get_output(interpreter,
score_threshold=threshold,
top_k=top_k)
arr_dur[1] = time.time() - start_t1
#cm.time_elapsed(start_t1,"inference")
#----------------------------------------------------
#-----------------other------------------------------------
start_t2 = time.time()
track_object(objs, labels) #tracking <<<<<<<
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2_im = append_text_img1(cv2_im, objs, labels, arr_dur,
arr_track_data)
ret, jpeg = cv2.imencode('.jpg', cv2_im)
pic = jpeg.tobytes()
#Flask streaming
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + pic + b'\r\n\r\n')
arr_dur[2] = time.time() - start_t2
fps = round(1.0 / (time.time() - start_time), 1)
print("*********FPS: ", fps, "************")
cap.release()
cv2.destroyAllWindows()
def script_env(script):
stdout = common.get_output(script)
return common.parse_output(stdout)
def capture(parse_args, interpreter, labels, camera_res):
""" Capture images from camera frames and write to disk. """
sample = 0
sample_time = 0
start_time = time.time()
try:
cap = cv2.VideoCapture(parse_args.camera_idx)
while cap.isOpened():
if sample > parse_args.num_samples:
break
elapsed_time = time.time() - sample_time
ret, frame = cap.read()
if not ret:
break
if elapsed_time > 1.0 / parse_args.frame_rate:
sample_time = time.time()
cv2_im = frame
cv2_im_u = cv2.undistort(cv2_im, common.CAMERA_MATRIX,
common.DIST_COEFFS)
cv2_im_u_rgb = cv2.cvtColor(cv2_im_u, cv2.COLOR_BGR2RGB)
pil_im = Image.fromarray(cv2_im_u_rgb)
common.set_input(interpreter, pil_im)
interpreter.invoke()
objs = common.get_output(interpreter,
score_threshold=parse_args.threshold,
labels=labels)
img_id = uuid.uuid4()
img_name = ''.join((str(img_id), '.jpg'))
for obj in objs:
if obj.label in parse_args.capture:
# Image may appear in more than one named directory
# if it contains more than one class of interest.
img_path = '{}'.format(
os.path.join(parse_args.images, obj.label,
img_name))
print('Found "{}" at t+ {:.2f} sec. Writing "{}".'.
format(obj.label, sample_time - start_time,
img_name))
cv2.imwrite(img_path, cv2_im_u)
sample += 1
if parse_args.display:
cv2_im_u = common.annotate_image(objs, camera_res,
cv2_im_u)
cv2.imshow('detections', cv2_im_u)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
except cv2.error as e:
print('cv2 error: {e}'.format(e))
except Exception as e:
print('Unhandled error: {e}'.format(e))
finally:
cap.release()
cv2.destroyAllWindows()
return
def script_env(script):
stdout = common.get_output(script)
return common.parse_output(stdout)
