def run(self):
# This method runs in a separate thread
global done, rawCapture
while not self.terminated:
# Wait for an image to be written to the stream
if self.event.wait(1):
try:
#self.stream.seek(0)
self.stream.readinto(rawCapture)
# Read the image and do some processing on it
#Image.open(self.stream)
#...
#...
self.frame_buf_val = np.frombuffer(self.stream.getvalue(),
dtype=np.uint8)
self.output = engine.DetectWithInputTensor(
self.frame_buf_val, top_k=10)
# Set done to True if you want the script to terminate
# at some point
#done=True
finally:
# Reset the stream and event
self.stream.seek(0)
self.stream.truncate()
self.event.clear()
# Return ourselves to the pool
with lock:
pool.append(self)
time.sleep(0.1)
while DISPLAY.loop_running():
fps_txt.draw()
ms_txt.draw()
ms = str(elapsed_ms*1000)
ms_txt.quick_change(ms)
i += 1
if i > N:
tm = time.time()
fps = "{:5.1f}FPS".format(i / (tm - last_tm))
fps_txt.quick_change(fps)
i = 0
last_tm = tm
#if new_pic:
results = engine.DetectWithInputTensor(g_input, top_k=4)
if new_pic:
if results:
num_obj = 0
for obj in results:
num_obj = num_obj + 1
buf = bbox.buf[0] # alias for brevity below
buf.array_buffer[:,:3] = 0.0;
for j, obj in enumerate(results):
coords = (obj.bounding_box - 0.5) * [[1.0, -1.0]] * mdl_dims # broadcasting will fix the arrays size differences
score = round(obj.score,2)
ix = 8 * j
buf.array_buffer[ix:(ix + 8), 0] = coords[X_IX, 0] + 2 * X_OFF
buf.array_buffer[ix:(ix + 8), 1] = coords[Y_IX, 1] + 2 * Y_OFF
buf.re_init(); #
new_pic = False
rgb = PiRGBArray(camera, size=camera.resolution * 3)
_, width, height, channels = engine.get_input_tensor_shape()
camera.start_preview(fullscreen=False,
layer=0,
window=(preview_mid_X, preview_mid_Y, preview_W,
preview_H))
try:
while DISPLAY.loop_running():
stream = io.BytesIO()
camera.capture(stream, use_video_port=True, format='bgr')
stream.truncate()
stream.seek(0)
input = np.frombuffer(stream.getvalue(), dtype=np.uint8)
#stream.close()
start_ms = time.time()
results = engine.DetectWithInputTensor(input, top_k=max_obj)
elapsed_ms = time.time() - start_ms
ms = str(int(elapsed_ms * 1000)) + "ms"
ms_txt.draw()
ms_txt.quick_change(ms)
fps_txt.draw()
i += 1
if i > N:
tm = time.time()
fps = "{:6.2f}FPS".format(i / (tm - last_tm))
fps_txt.quick_change(fps)
i = 0
last_tm = tm
if results:
num_obj = 0
for obj in results:
fps = "00.0 fps"
N = 10
ms = "00"
while True:
print("started the loop of draemes")
screen = pygame.display.get_surface(
) #get the surface of the current active display
resized_x, resized_y = mdl_dims, mdl_dims #screen.get_width(), screen.get_height()
img = pycam.get_image()
img = pygame.transform.scale(img, (resized_x, resized_y))
screen.blit(img, (0, 0))
if new_pic:
start_ms = time.time()
results = engine.DetectWithInputTensor(frame_buf_val,
threshold=thresh,
top_k=max_obj)
elapsed_ms = time.time() - start_ms
#pygame.surfarray.blit_array(screen, img_arr)
i += 1
if results:
num_obj = 0
for obj in results:
num_obj = num_obj + 1
for obj in results:
bbox = obj.bounding_box.flatten().tolist()
label_id = int(round(obj.label_id, 1))
class_label = "%s" % (labels[label_id])
fnt_class_label = fnt.render(class_label, True,
(255, 255, 255))
fnt_class_label_width = fnt_class_label.get_rect().width
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model',
help='File path of Tflite model.',
default=
"/home/rock64/models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite"
)
parser.add_argument('--labels',
help="Path of the labels file.",
default="/home/rock64/detection/coco_labels.txt")
parser.add_argument('--dims', help='Model input dimension', default=320)
parser.add_argument('--max_obj',
help='Maximum objects detected [>= 1], default=10',
default=10)
parser.add_argument('--thresh',
help='Threshold confidence [0.1-1.0], default=0.3',
default=0.3)
parser.add_argument('--video_off',
help='Video display off, for increased FPS',
action='store_true',
default=False)
parser.add_argument(
'--cam_w',
help=
'Set camera resolution, examples: 96, 128, 256, 352, 384, 480, 640, 1920',
default=320)
parser.add_argument(
'--cam_h',
help=
'Set camera resolution, examples: 96, 128, 256, 352, 384, 480, 640, 1920',
default=320)
if len(sys.argv[0:]) == 0:
parser.print_help()
#parser.print_usage() # for just the usage line
parser.exit()
args = parser.parse_args()
if args.labels:
with open(args.labels, 'r') as f:
pairs = (l.strip().split(maxsplit=1) for l in f.readlines())
labels = dict((int(k), v) for k, v in pairs)
else:
lbl_input = input("Type label name for this single class model:")
if lbl_input:
labels = {0: lbl_input}
else:
labels = {0: 'object'}
mdl_dims = int(args.dims)
max_obj = int(args.max_obj)
cam_w = int(args.cam_w)
cam_h = int(args.cam_h)
thresh = float(args.thresh)
video_off = args.video_off
engine = edgetpu.detection.engine.DetectionEngine(args.model)
pygame.init()
pygame.camera.init()
if not video_off:
screen = pygame.display.set_mode(
(cam_w, cam_h), pygame.HWSURFACE + pygame.HWACCEL +
pygame.DOUBLEBUF) #+pygame.ASYNCBLIT,16)
pygame.display.set_caption('Object Detection')
pygame.font.init()
fnt_sz = 18
fnt = pygame.font.SysFont('Arial', fnt_sz)
camlist = pygame.camera.list_cameras()
if camlist:
pycam = pygame.camera.Camera(camlist[0], (cam_w, cam_h))
else:
print("No camera found!")
exit
pycam.start()
time.sleep(1)
x1 = x2 = y1 = y2 = i = j = fps_last = fps_total = 0
start_ms = last_tm = elapsed_ms = time.time()
results = None
fps_avg = "00.0"
N = 10
ms = "00"
scale_req = False
if (cam_w != mdl_dims) or (cam_h != mdl_dims):
scale_req = True
#if not video_off :
# screen = pygame.display.get_surface() #get the surface of the current active display
# screen_x,screen_y = screen.get_width(), screen.get_height()
img = pycam.get_image()
img = pygame.transform.scale(img, (mdl_dims, mdl_dims))
while True:
#if not video_off :
#screen = pygame.display.get_surface() #get the surface of the current active display
#scr_w,scr_h = screen.get_width(), screen.get_height()
if pycam.query_image():
#grab image from camera, when available
img = pycam.get_image()
if not video_off:
if scale_req:
img = pygame.transform.scale(img, (cam_w, cam_h))
screen.blit(img, (0, 0))
detect_img = pygame.transform.scale(
img, (mdl_dims, mdl_dims))
else:
screen.blit(img, (0, 0))
detect_img = img
else:
if scale_req:
detect_img = pygame.transform.scale(
img, (mdl_dims, mdl_dims))
else:
detect_img = img
img_arr = pygame.surfarray.pixels3d(detect_img)
img_arr = np.swapaxes(img_arr, 0, 1)
img_arr = np.ascontiguousarray(img_arr)
frame = io.BytesIO(img_arr)
frame_buf_val = np.frombuffer(frame.getvalue(), dtype=np.uint8)
start_ms = time.time()
results = engine.DetectWithInputTensor(frame_buf_val,
threshold=thresh,
top_k=max_obj)
elapsed_ms = time.time() - start_ms
i += 1
if results:
obj_cnt = 0
obj_id = 0
for obj in results:
obj_cnt += 1
for obj in results:
obj_id += 1
bbox = obj.bounding_box.flatten().tolist()
label_id = int(round(obj.label_id, 1))
class_label = "%s" % (labels[label_id])
score = round(obj.score, 2)
x1 = round(bbox[0] * cam_w)
y1 = round(bbox[1] * cam_h)
x2 = round(bbox[2] * cam_w)
y2 = round(bbox[3] * cam_h)
rect_width = x2 - x1
rect_height = y2 - y1
class_score = "%.2f" % (score)
if not video_off:
fnt_class_score = fnt.render(class_score, True,
(0, 255, 255))
fnt_class_score_width = fnt_class_score.get_rect(
).width
screen.blit(fnt_class_score,
(x2 - fnt_class_score_width, y1 - fnt_sz))
fnt_class_label = fnt.render(class_label, True,
(255, 255, 255))
fnt_class_label_width = fnt_class_label.get_rect(
).width
screen.blit(fnt_class_label, (x1, y1 - fnt_sz))
fnt_ms = fnt.render(ms, True, (255, 255, 255))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,
((cam_w / 2) - (fnt_ms_width / 2), 0))
bbox_rect = pygame.draw.rect(
screen, (0, 255, 0),
(x1, y1, rect_width, rect_height), 4)
if i > N:
ms = "(%d%s%d) %s%.2fms" % (obj_cnt, "/", max_obj,
"objects detected in ",
elapsed_ms * 1000)
print(ms)
output = "%s%d %s%s %s%s %s%d %s%d %s%d %s%d %s" % (
"id:", obj_id, "class:", class_label, "conf:",
class_score, "x1:", x1, "y1:", y1, "x2:", x2, "y2:",
y2, fps_avg)
print(output)
else:
if i > N:
ms = "%s %.2fms" % ("No objects detected in",
elapsed_ms * 1000)
print(ms)
if not video_off:
fnt_ms = fnt.render(ms, True, (255, 0, 0))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms, ((cam_w / 2) - (fnt_ms_width / 2), 0))
if i > N:
tm = time.time()
fps_last = i / (tm - last_tm)
if j < 5:
j += 1
fps_total = fps_total + fps_last
else:
fps_avg = "AVG_FPS:{:5.1f} ".format(fps_total / 5)
fps_total = 0
j = 0
i = 0
last_tm = tm
if not video_off:
fps_thresh = fps_avg + " thresh:" + str(thresh)
fps_fnt = fnt.render(fps_thresh, True, (255, 255, 0))
fps_width = fps_fnt.get_rect().width
screen.blit(fps_fnt, ((cam_w / 2) - (fps_width / 2), 20))
for event in pygame.event.get():
keys = pygame.key.get_pressed()
if (keys[pygame.K_ESCAPE] == 1):
pycam.stop()
pygame.display.quit()
sys.exit()
#elif event.type == pygame.VIDEORESIZE and not video_off:
# screen = pygame.display.set_mode((event.w,event.h),pygame.RESIZABLE)
if not video_off:
pygame.display.update()
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--model',
help='File path of Tflite model.',
required=True)
parser.add_argument(
'--labels',
help='labels file path OR no arg will prompt for label name',
required=False)
parser.add_argument('--dims', help='Model input dimension', required=True)
parser.add_argument('--max_obj',
help='Maximum objects detected [>= 1], default=1',
default=1,
required=False)
parser.add_argument('--thresh',
help='Threshold confidence [0.1-1.0], default=0.3',
default=0.3,
required=False)
parser.add_argument('--video_off',
help='Video display on/off, for increased FPS',
action='store_true',
required=False)
parser.add_argument(
'--cam_res_x',
help=
'Set camera X resolution, examples: 96, 128, 256, 352, 384, 480, 640, 1920',
default=320,
required=False)
parser.add_argument(
'--cam_res_y',
help=
'Set camera Y resolution, examples: 96, 128, 256, 352, 384, 480, 640, 1920',
default=320,
required=False)
if len(sys.argv[0:]) == 0:
parser.print_help()
#parser.print_usage() # for just the usage line
parser.exit()
args = parser.parse_args()
if args.labels:
with open(args.labels, 'r') as f:
pairs = (l.strip().split(maxsplit=1) for l in f.readlines())
labels = dict((int(k), v) for k, v in pairs)
else:
lbl_input = input("Type label name for this single object model:")
if lbl_input:
labels = {0: lbl_input}
else:
labels = {0: 'object'}
mdl_dims = int(args.dims)
if args.max_obj:
max_obj = int(args.max_obj)
if max_obj < 1:
max_obj = 1
if args.thresh:
thresh = float(args.thresh)
if thresh < 0.1 or thresh > 1.0:
thresh = 0.3
video_off = False
if args.video_off:
video_off = True
if args.cam_res_x:
cam_res_x = int(args.cam_res_x)
else:
cam_res_x = 320
if args.cam_res_y:
cam_res_y = int(args.cam_res_y)
else:
cam_res_y = 320
#c = threading.Condition()
#frame_buf_val = None
engine = edgetpu.detection.engine.DetectionEngine(args.model)
pygame.init()
pygame.camera.init()
camlist = pygame.camera.list_cameras()
if camlist:
pycam = pygame.camera.Camera(camlist[0], (cam_res_x, cam_res_y))
pycam.start()
time.sleep(2)
else:
print("No camera found!")
exit
if video_off == False:
screen = pygame.display.set_mode((cam_res_x, cam_res_y),
pygame.RESIZABLE)
pygame.display.set_caption('Object Detection')
screen = pygame.display.get_surface(
) #get the surface of the current active display
resized_x, resized_y = size = screen.get_width(), screen.get_height()
pygame.font.init()
fnt_sz = 18
fnt = pygame.font.SysFont('Arial', fnt_sz)
lbl_fnt_sz = 10
lbl_fnt = pygame.font.SysFont('Arial', lbl_fnt_sz)
x1 = x2 = y1 = y2 = 0
last_tm = time.time()
start_ms = time.time()
elapsed_ms = time.time()
i = 0
results = None
fps = "00.0 fps"
N = 10
ms = "00"
#py_thread = PyThread().start()
#detection_thread = Detection(args.model).start()
while True:
start_ms = time.time()
#if pycam.query_image():
img = pycam.get_image()
#img = pycam.get_image()
if video_off == False:
img = pygame.transform.scale(img, (resized_x, resized_y))
screen.blit(img, (0, 0))
detect_img = pygame.transform.scale(img, (mdl_dims, mdl_dims))
img_arr = pygame.surfarray.pixels3d(img)
img_arr = np.swapaxes(img_arr, 0, 1)
img_arr = np.ascontiguousarray(img_arr)
frame = io.BytesIO(img_arr)
frame_buf_val = np.frombuffer(frame.getvalue(), dtype=np.uint8)
#print(frame_buf_val)
#start_ms = time.time()
#results = detection_thread.get_results()
results = engine.DetectWithInputTensor(frame_buf_val,
threshold=thresh,
top_k=max_obj)
#elapsed_ms = time.time() - start_ms
#pygame.surfarray.blit_array(screen, img_arr)
if i > 5:
tm = time.time()
fps = "fps:{:5.1f} ".format(i / (tm - last_tm))
i = 0
last_tm = tm
i += 1
if results:
num_obj = 0
for obj in results:
bbox = obj.bounding_box.flatten().tolist()
label_id = int(round(obj.label_id, 1))
class_label = "%s" % (labels[label_id])
score = round(obj.score, 2)
class_score = "%.2f" % (score)
if video_off == False:
x1 = round(bbox[0] * resized_x)
y1 = round(bbox[1] * resized_y)
x2 = round(bbox[2] * resized_x)
y2 = round(bbox[3] * resized_y)
rect_width = x2 - x1
rect_height = y2 - y1
fnt_class_label = lbl_fnt.render(class_label, True,
(255, 255, 255))
fnt_class_label_width = fnt_class_label.get_rect().width
screen.blit(fnt_class_label, (x1, y1 - lbl_fnt_sz))
fnt_class_score = lbl_fnt.render(class_score, True,
(0, 255, 255))
fnt_class_score_width = fnt_class_score.get_rect().width
screen.blit(fnt_class_score,
(x2 - fnt_class_score_width, y1 - lbl_fnt_sz))
bbox_rect = pygame.draw.rect(
screen, (0, 255, 0), (x1, y1, rect_width, rect_height),
4)
results_line = "%d, %s, %s, %d,%d,%d,%d" % (
num_obj, class_label, class_score, x1, y1, x2, y2)
print(results_line)
elapsed_ms = time.time() - start_ms
if i > N:
ms = "(%d%s%d) %s%.2fms" % (num_obj, "/", max_obj,
"objects detected in ",
elapsed_ms * 1000)
fnt_ms = fnt.render(ms, True, (255, 255, 255))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,
((resized_x / 2) - (fnt_ms_width / 2), 0))
else: #video_off == True
x1 = round(bbox[0] * mdl_dims)
y1 = round(bbox[1] * mdl_dims)
x2 = round(bbox[2] * mdl_dims)
y2 = round(bbox[3] * mdl_dims)
results_line = "%s, %d, %s, %s, %d,%d,%d,%d" % (
fps, num_obj, class_label, class_score, x1, y1, x2, y2)
print(results_line)
num_obj = num_obj + 1
else:
if video_off == False:
elapsed_ms = time.time() - start_ms
if i > N:
ms = "%s %.2fms" % ("No objects detected in",
elapsed_ms * 1000)
fnt_ms = fnt.render(ms, True, (255, 0, 0))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms, ((resized_x / 2) - (fnt_ms_width / 2), 0))
else:
print("No results")
if video_off == False:
fps_thresh = fps + " thresh:" + str(thresh)
fps_fnt = fnt.render(fps_thresh, True, (255, 255, 0))
fps_width = fps_fnt.get_rect().width
screen.blit(fps_fnt, ((resized_x / 2) - (fps_width / 2), 20))
pygame.display.update()
for event in pygame.event.get():
keys = pygame.key.get_pressed()
if (keys[pygame.K_ESCAPE] == 1):
#pycam.stop()
#pygame.display.quit()
pygame.quit()
sys.exit()
elif event.type == pygame.VIDEORESIZE:
screen = pygame.display.set_mode((event.w, event.h),
pygame.RESIZABLE)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model', help='File path of Tflite model.', required=True)
parser.add_argument(
'--dims', help='Model input dimension', required=True)
args = parser.parse_args()
#Set all input params equal to the input dimensions expected by the model
mdl_dims = int(args.dims) #dims must be a factor of 32 for picamera resolution to work
#Set max num of objects you want to detect per frame
max_obj = 10
engine = edgetpu.detection.engine.DetectionEngine(args.model)
pygame.init()
pygame.display.set_caption('Face Detection')
screen = pygame.display.set_mode((mdl_dims, mdl_dims), pygame.DOUBLEBUF|pygame.HWSURFACE)
pygame.font.init()
fnt_sz = 18
myfont = pygame.font.SysFont('Arial', fnt_sz)
camera = picamera.PiCamera()
strm_thread = PiVideoStream().start()
strm_thread.rgbCapture = bytearray(strm_thread.camera.resolution[0] * strm_thread.camera.resolution[1] * 3)
#Set camera resolution equal to model dims
camera.resolution = (mdl_dims, mdl_dims)
#rgb = bytearray(camera.resolution[0] * camera.resolution[1] * 3)
camera.framerate = 30
_, width, height, channels = engine.get_input_tensor_shape()
x1, x2, x3, x4, x5 = 0, 50, 50, 0, 0
y1, y2, y3, y4, y5 = 50, 50, 0, 0, 50
z = 5
last_tm = time.time()
i = 0
exitFlag = True
while(exitFlag):
for event in pygame.event.get():
keys = pygame.key.get_pressed()
if(keys[pygame.K_ESCAPE] == 1):
exitFlag = False
with picamera.array.PiRGBArray(camera, size=(mdl_dims, mdl_dims)) as stream:
#stream = io.BytesIO()
start_ms = time.time()
camera.capture(stream, use_video_port=True, format='rgb')
elapsed_ms = time.time() - start_ms
stream.seek(0)
stream.readinto(stream.rgbCapture)
#stream.truncate() #needed??
img = pygame.image.frombuffer(stream.rgbCapture[0:
(camera.resolution[0] * camera.resolution[1] * 3)],
camera.resolution, 'RGB')
input = np.frombuffer(stream.getvalue(), dtype=np.uint8)
#Inference
results = engine.DetectWithInputTensor(input, top_k=max_obj)
stream.close()
if img:
screen.blit(img, (0,0))
if results:
num_obj = 0
for obj in results:
num_obj = num_obj + 1
for obj in results:
bbox = obj.bounding_box.flatten().tolist()
score = round(obj.score,2)
x1 = round(bbox[0] * mdl_dims)
y1 = round(bbox[1] * mdl_dims)
x2 = round(bbox[2] * mdl_dims)
y2 = round(bbox[3] * mdl_dims)
rect_width = x2 - x1
rect_height = y2 - y1
class_score = "%.2f" % (score)
ms = "(%d) %s%.2fms" % (num_obj, "faces detected in ", elapsed_ms*1000)
fnt_class_score = myfont.render(class_score, True, (0,0,255))
fnt_class_score_width = fnt_class_score.get_rect().width
screen.blit(fnt_class_score,(x1, y1-fnt_sz))
fnt_ms = myfont.render(ms, True, (255,255,255))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,((mdl_dims / 2) - (fnt_ms_width / 2), 0))
bbox_rect = pygame.draw.rect(screen, (0,0,255), (x1, y1, rect_width, rect_height), 2)
#pygame.display.update(bbox_rect)
else:
elapsed_ms = time.time() - start_ms
ms = "%s %.2fms" % ("No faces detected in", elapsed_ms*1000)
fnt_ms = myfont.render(ms, True, (255,0,0))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,((mdl_dims / 2) - (fnt_ms_width / 2), 0))
pygame.display.update()
pygame.display.quit()
def start_capture(): # has to be in yet another thread as blocking
global mdl_dims, pool, engine, results, screen, start_ms, elapsed_ms, fnt_sz, preview_mid_X, preview_mid_Y, camera, rgb, max_obj
x1, x2, x3, x4, x5 = 0, 50, 50, 0, 0
y1, y2, y3, y4, y5 = 50, 50, 0, 0, 50
z = 5
pygame.init()
pygame.display.set_caption('Face Detection')
screen = pygame.display.set_mode((mdl_dims, mdl_dims),
pygame.DOUBLEBUF | pygame.HWSURFACE)
pygame.font.init()
fnt_sz = 18
myfont = pygame.font.SysFont('Arial', fnt_sz)
x1, x2, x3, x4, x5 = 0, 50, 50, 0, 0
y1, y2, y3, y4, y5 = 50, 50, 0, 0, 50
z = 5
last_tm = time.time()
i = 0
exitFlag = True
while (exitFlag):
for event in pygame.event.get():
keys = pygame.key.get_pressed()
if (keys[pygame.K_ESCAPE] == 1):
exitFlag = False
with picamera.PiCamera() as camera:
pool = [ImageProcessor() for i in range(4)]
camera.resolution = (mdl_dims, mdl_dims)
rgb = bytearray(camera.resolution[0] * camera.resolution[1] * 3)
camera.framerate = 24
with picamera.array.PiRGBArray(camera, size=(mdl_dims,
mdl_dims)) as stream:
start_ms = time.time()
camera.capture_sequence(streams(),
format='rgb',
use_video_port=True)
elapsed_ms = time.time() - start_ms
#Inference
results = engine.DetectWithInputTensor(input, top_k=max_obj)
img = pygame.image.frombuffer(
rgb[0:(camera.resolution[0] * camera.resolution[1] * 3)],
camera.resolution, 'RGB')
if img:
screen.blit(img, (0, 0))
if results:
num_obj = 0
for obj in results:
num_obj = num_obj + 1
for obj in results:
bbox = obj.bounding_box.flatten().tolist()
score = round(obj.score, 2)
x1 = round(bbox[0] * mdl_dims)
y1 = round(bbox[1] * mdl_dims)
x2 = round(bbox[2] * mdl_dims)
y2 = round(bbox[3] * mdl_dims)
rect_width = x2 - x1
rect_height = y2 - y1
class_score = "%.2f" % (score)
ms = "(%d) %s%.2fms" % (num_obj,
"faces detected in ",
elapsed_ms * 1000)
fnt_class_score = myfont.render(
class_score, True, (0, 0, 255))
fnt_class_score_width = fnt_class_score.get_rect(
).width
screen.blit(fnt_class_score, (x1, y1 - fnt_sz))
fnt_ms = myfont.render(ms, True, (255, 255, 255))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms, ((mdl_dims / 2) -
(fnt_ms_width / 2), 0))
bbox_rect = pygame.draw.rect(
screen, (0, 0, 255),
(x1, y1, rect_width, rect_height), 2)
#pygame.display.update(bbox_rect)
else:
elapsed_ms = time.time() - start_ms
ms = "%s %.2fms" % ("No faces detected in",
elapsed_ms * 1000)
fnt_ms = myfont.render(ms, True, (255, 0, 0))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,
((mdl_dims / 2) - (fnt_ms_width / 2), 0))
pygame.display.update()
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model', help='File path of Tflite model.', required=True)
parser.add_argument(
'--labels', help='File path of labels file OR leave empty for prompt to type label name', required=False)
parser.add_argument(
'--dims', help='Model input dimension', required=True)
parser.add_argument(
'--max_obj', help='Maximum objects detected [>= 1], default=1', default=1, required=False)
parser.add_argument(
'--thresh', help='Threshold confidence [0.1-1.0], default=0.3', default=0.3, required=False)
parser.add_argument(
'--video_off', help='Video display off, for increased FPS', action='store_true', required=False)
if len(sys.argv[0:])==0:
parser.print_help()
#parser.print_usage() # for just the usage line
parser.exit()
args = parser.parse_args()
if args.labels:
with open(args.labels, 'r') as f:
pairs = (l.strip().split(maxsplit=1) for l in f.readlines())
labels = dict((int(k), v) for k, v in pairs)
else:
lbl_input = None
lbl_input = input("Type label name for this single object model:")
if lbl_input == None:
labels = ["Object"]
else:
labels = [lbl_input]
mdl_dims = int(args.dims)
if args.max_obj:
max_obj = int(args.max_obj)
if max_obj < 1:
max_obj = 1
if args.thresh:
thresh = float(args.thresh)
if thresh < 0.1 or thresh > 1.0:
thresh = 0.3
#else:
# thresh = 0.3
video_off = False
if args.video_off :
video_off = True
cam_res_x = 256
cam_res_y = 256
max_fps = 30
engine = edgetpu.detection.engine.DetectionEngine(args.model)
pygame.init()
pygame.camera.init()
#screen = pygame.display.set_mode((mdl_dims, mdl_dims), pygame.DOUBLEBUF|pygame.HWSURFACE)
screen = pygame.display.set_mode((mdl_dims,mdl_dims), pygame.RESIZABLE)
pygame.display.set_caption('Object Detection')
pycam = pygame.camera.Camera("/dev/video0",(cam_res_x,cam_res_y)) #, "RGB")
pycam.start()
#screen.convert()
clock = pygame.time.Clock()
##camera = picamera.PiCamera()
##camera.resolution = (mdl_dims, mdl_dims)
##camera.framerate = max_fps
pygame.font.init()
fnt_sz = 18
fnt = pygame.font.SysFont('Arial', fnt_sz)
x1=x2=y1=y2=0
#x1, x2, x3, x4, x5 = 0, 50, 50, 0, 0
#y1, y2, y3, y4, y5 = 50, 50, 0, 0, 50
#z = 5
last_tm = time.time()
start_ms = time.time()
elapsed_ms = time.time()
i = 0
results = None
fps = "00.0 fps"
N = 10
##rgb = bytearray(camera.resolution[0] * camera.resolution[1] * 3)
#rgb = bytearray(320 * 320 * 3)
#rawCapture = PiRGBArray(camera, size=camera.resolution)
#stream = camera.capture_continuous(rawCapture, format="rgb", use_video_port=True)
while True:
#clock.tick(max_fps)
#with picamera.array.PiRGBArray(camera, size=(mdl_dims, mdl_dims)) as stream:
#for foo in camera.capture_continuous(stream, use_video_port=True, format='rgb'):
#for f in stream:
#start_ms = time.time()
#frame = io.BytesIO(f.array)
#frame_buf_val = np.frombuffer(frame.getvalue(), dtype=np.uint8)
#results = engine.DetectWithInputTensor(frame_buf_val, top_k=10)
#rawCapture.truncate(0)
#elapsed_ms = time.time() - start_ms
##stream = io.BytesIO()
##camera.capture(stream, use_video_port=True, format='rgb')
##stream.seek(0)
##stream.readinto(rgb)
##frame_val = np.frombuffer(stream.getvalue(), dtype=np.uint8)
##start_ms = time.time()
##results = engine.DetectWithInputTensor(frame_val, top_k=max_obj)
##elapsed_ms = time.time() - start_ms
##img = pygame.image.frombuffer(rgb[0:
##(camera.resolution[0] * camera.resolution[1] * 3)],
##camera.resolution, 'RGB')
img = pycam.get_image()
img = pygame.transform.scale(img,(mdl_dims,mdl_dims))
img_arr = pygame.surfarray.pixels3d(img)
img_arr = np.swapaxes(img_arr,0,1)
#img_arr = pygame.PixelArray.transpose(img_arr) #requires pygame.PixelArray object
img_arr = np.ascontiguousarray(img_arr)
frame = io.BytesIO(img_arr)
frame_buf_val = np.frombuffer(frame.getvalue(), dtype=np.uint8)
#print(frame_buf_val)
start_ms = time.time()
results = engine.DetectWithInputTensor(frame_buf_val, threshold=thresh, top_k=max_obj)
#frame.truncate(0)
elapsed_ms = time.time() - start_ms
screen = pygame.display.get_surface() #get the surface of the current active display
resized_x,resized_y = size = screen.get_width(), screen.get_height()
#print("x:", resized_x, " y:", resized_y)
img = pygame.transform.scale(img,(resized_x, resized_y))
if img and video_off == False:
screen.blit(img, (0,0))
#pygame.surfarray.blit_array(screen, img_arr)
i += 1
if i > N:
tm = time.time()
fps = "fps:{:5.1f} ".format(i / (tm - last_tm))
i = 0
last_tm = tm
fps_thresh = fps + " thresh:" + str(thresh)
fps_fnt = fnt.render(fps_thresh, True, (255,255,0))
fps_width = fps_fnt.get_rect().width
screen.blit(fps_fnt,((resized_x / 2) - (fps_width / 2), 20))
if results:
num_obj = 0
for obj in results:
num_obj = num_obj + 1
for obj in results:
bbox = obj.bounding_box.flatten().tolist()
label_id = int(round(obj.label_id,1))
class_label = "%s" % (labels[label_id])
fnt_class_label = fnt.render(class_label, True, (255,255,255))
fnt_class_label_width = fnt_class_label.get_rect().width
screen.blit(fnt_class_label,(x1, y1-fnt_sz))
score = round(obj.score,2)
x1 = round(bbox[0] * resized_x)
y1 = round(bbox[1] * resized_y)
x2 = round(bbox[2] * resized_x)
y2 = round(bbox[3] * resized_y)
rect_width = x2 - x1
rect_height = y2 - y1
class_score = "%.2f" % (score)
fnt_class_score = fnt.render(class_score, True, (0,255,255))
fnt_class_score_width = fnt_class_score.get_rect().width
screen.blit(fnt_class_score,(x2-fnt_class_score_width, y1-fnt_sz))
ms = "(%d%s%d) %s%.2fms" % (num_obj, "/", max_obj, "objects detected in ", elapsed_ms*1000)
fnt_ms = fnt.render(ms, True, (255,255,255))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,((resized_x / 2 ) - (fnt_ms_width / 2), 0))
bbox_rect = pygame.draw.rect(screen, (0,255,0), (x1, y1, rect_width, rect_height), 4)
else:
ms = "%s %.2fms" % ("No objects detected in", elapsed_ms*1000)
fnt_ms = fnt.render(ms, True, (255,0,0))
fnt_ms_width = fnt_ms.get_rect().width
screen.blit(fnt_ms,((resized_x / 2 ) - (fnt_ms_width / 2), 0))
for event in pygame.event.get():
keys = pygame.key.get_pressed()
if(keys[pygame.K_ESCAPE] == 1):
pycam.stop()
#pygame.quit()
##camera.close()
pygame.display.quit()
sys.exit()
elif event.type == pygame.VIDEORESIZE:
screen = pygame.display.set_mode((event.w,event.h),pygame.RESIZABLE)
#pygame.display.flip()
pygame.display.update()