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#!/usr/bin/env python | |
""" | |
Copyright (c) 2018 Intel Corporation | |
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 | |
http://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. | |
""" | |
from __future__ import print_function | |
import sys | |
import os | |
from argparse import ArgumentParser | |
import cv2 | |
import time | |
import logging as log | |
from openvino.inference_engine import IENetwork, IEPlugin | |
from timeit import default_timer as timer | |
def build_argparser(): | |
parser = ArgumentParser() | |
parser.add_argument( | |
"-m", | |
"--model", | |
help="Path to an .xml file with a trained model.", | |
required=True, | |
type=str) | |
parser.add_argument( | |
"-i", | |
"--input", | |
help="Path to video file or image. 'cam' for capturing video stream from camera", | |
required=True, | |
type=str) | |
parser.add_argument( | |
"-l", | |
"--cpu_extension", | |
help="MKLDNN (CPU)-targeted custom layers.Absolute path to a shared library with the kernels " | |
"impl.", | |
type=str, | |
default=None) | |
parser.add_argument( | |
"-pp", | |
"--plugin_dir", | |
help="Path to a plugin folder", | |
type=str, | |
default=None) | |
parser.add_argument( | |
"-d", | |
"--device", | |
help="Specify the target device to infer on; CPU, GPU, FPGA or MYRIAD is acceptable. Demo " | |
"will look for a suitable plugin for device specified (CPU by default)", | |
default="CPU", | |
type=str) | |
parser.add_argument( | |
"--labels", help="Labels mapping file", default=None, type=str) | |
parser.add_argument( | |
"-pt", | |
"--prob_threshold", | |
help="Probability threshold for detections filtering", | |
default=0.5, | |
type=float) | |
return parser | |
def main(): | |
log.basicConfig( | |
format="[ %(levelname)s ] %(message)s", | |
level=log.INFO, | |
stream=sys.stdout) | |
args = build_argparser().parse_args() | |
model_xml = args.model | |
model_bin = os.path.splitext(model_xml)[0] + ".bin" | |
# Plugin initialization for specified device and load extensions library if specified | |
log.info("Initializing plugin for {} device...".format(args.device)) | |
plugin = IEPlugin(device=args.device, plugin_dirs=args.plugin_dir) | |
if args.cpu_extension and 'CPU' in args.device: | |
plugin.add_cpu_extension(args.cpu_extension) | |
# Read IR | |
log.info("Reading IR...") | |
net = IENetwork(model=model_xml, weights=model_bin) | |
if plugin.device == "CPU": | |
supported_layers = plugin.get_supported_layers(net) | |
not_supported_layers = [ | |
l for l in net.layers.keys() if l not in supported_layers | |
] | |
if len(not_supported_layers) != 0: | |
log.error( | |
"Following layers are not supported by the plugin for specified device {}:\n {}". | |
format(plugin.device, ', '.join(not_supported_layers))) | |
log.error( | |
"Please try to specify cpu extensions library path in demo's command line parameters using -l " | |
"or --cpu_extension command line argument") | |
sys.exit(1) | |
assert len( | |
net.inputs.keys()) == 1, "Demo supports only single input topologies" | |
assert len(net.outputs) == 1, "Demo supports only single output topologies" | |
input_blob = next(iter(net.inputs)) | |
out_blob = next(iter(net.outputs)) | |
log.info("Loading IR to the plugin...") | |
exec_net = plugin.load(network=net, num_requests=2) | |
# Read and pre-process input image | |
n, c, h, w = net.inputs[input_blob].shape | |
del net | |
if args.input == 'cam': | |
input_stream = 0 | |
else: | |
input_stream = args.input | |
assert os.path.isfile(args.input), "Specified input file doesn't exist" | |
if args.labels: | |
with open(args.labels, 'r') as f: | |
labels_map = [x.strip() for x in f] | |
else: | |
labels_map = None | |
#cap = cv2.imread(input_stream) | |
cap = cv2.VideoCapture(input_stream) | |
cur_request_id = 0 | |
next_request_id = 1 | |
log.info("Starting inference in async mode...") | |
log.info("To switch between sync and async modes press Tab button") | |
log.info("To stop the demo execution press Esc button") | |
is_async_mode = True | |
render_time = 0 | |
ret, frame = cap.read() | |
## | |
accum_time = 0 | |
curr_fps = 0 | |
fps = "FPS: ??" | |
prev_time = timer() | |
while cap.isOpened(): | |
if is_async_mode: | |
ret, next_frame = cap.read() | |
else: | |
ret, frame = cap.read() | |
if not ret: | |
break | |
initial_w = cap.get(3) | |
initial_h = cap.get(4) | |
# Main sync point: | |
# in the truly Async mode we start the NEXT infer request, while waiting for the CURRENT to complete | |
# in the regular mode we start the CURRENT request and immediately wait for it's completion | |
inf_start = time.time() | |
if is_async_mode: | |
in_frame = cv2.resize(next_frame, (w, h)) | |
in_frame = in_frame.transpose( | |
(2, 0, 1)) # Change data layout from HWC to CHW | |
in_frame = in_frame.reshape((n, c, h, w)) | |
exec_net.start_async( | |
request_id=next_request_id, inputs={input_blob: in_frame}) | |
else: | |
in_frame = cv2.resize(frame, (w, h)) | |
in_frame = in_frame.transpose( | |
(2, 0, 1)) # Change data layout from HWC to CHW | |
in_frame = in_frame.reshape((n, c, h, w)) | |
if exec_net.requests[cur_request_id].wait(-1) == 0: | |
exec_net.start_async( | |
request_id=cur_request_id, inputs={input_blob: in_frame}) | |
if exec_net.requests[cur_request_id].wait(-1) == 0: | |
inf_end = time.time() | |
det_time = inf_end - inf_start | |
# Parse detection results of the current request | |
res = exec_net.requests[cur_request_id].outputs[out_blob] | |
for obj in res[0][0]: | |
# Draw only objects when probability more than specified threshold | |
if obj[2] > args.prob_threshold: | |
xmin = int(obj[3] * initial_w) | |
ymin = int(obj[4] * initial_h) | |
xmax = int(obj[5] * initial_w) | |
ymax = int(obj[6] * initial_h) | |
class_id = int(obj[1]) | |
# Draw box and label\class_id | |
##color = (min(class_id * 12.5, 255), min(class_id * 7, 255), min(class_id * 5, 255)) | |
color = (0, 255, 0) | |
cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), color, 2) | |
det_label = labels_map[class_id] if labels_map else str( | |
class_id) | |
cv2.putText( | |
frame, | |
det_label + ' ' + str(round(obj[2] * 100, 1)) + ' %', | |
(xmin, ymin - 7), cv2.FONT_HERSHEY_COMPLEX, 0.6, color, | |
2) | |
# Draw performance stats | |
inf_time_message = "Inference time: N\A for async mode" if is_async_mode else \ | |
"Inference time: {:.3f} ms".format(det_time * 1000) | |
render_time_message = "OpenCV rendering time: {:.3f} ms".format( | |
render_time * 1000) | |
async_mode_message = "Async mode is on. Processing request {}".format(cur_request_id) if is_async_mode else \ | |
"Async mode is off. Processing request {}".format(cur_request_id) | |
## | |
frame = cv2.resize(frame, (w, h)) | |
cv2.putText(frame, inf_time_message, (15, 15), | |
cv2.FONT_HERSHEY_COMPLEX, 0.5, (200, 10, 10), 1) | |
cv2.putText(frame, render_time_message, (15, 30), | |
cv2.FONT_HERSHEY_COMPLEX, 0.5, (10, 10, 200), 1) | |
cv2.putText(frame, async_mode_message, (10, int(initial_h - 20)), | |
cv2.FONT_HERSHEY_COMPLEX, 0.5, (10, 10, 200), 1) | |
## ref. https://github.com/rykov8/ssd_keras/blob/master/testing_utils/videotest.py | |
# Calculate FPS | |
# This computes FPS for everything, not just the model's execution | |
# which may or may not be what you want | |
curr_time = timer() | |
exec_time = curr_time - prev_time | |
prev_time = curr_time | |
accum_time = accum_time + exec_time | |
curr_fps = curr_fps + 1 | |
if accum_time > 1: | |
accum_time = accum_time - 1 | |
fps = "FPS: " + str(curr_fps) | |
curr_fps = 0 | |
# Draw FPS in top left corner | |
cv2.rectangle(frame, (w - 50, 0), (w, 17), (255, 255, 255), -1) | |
cv2.putText(frame, fps, (w - 50 + 3, 10), cv2.FONT_HERSHEY_SIMPLEX, | |
0.35, (0, 0, 0), 1) | |
# | |
render_start = time.time() | |
cv2.imshow("Detection Results", frame) | |
render_end = time.time() | |
render_time = render_end - render_start | |
if is_async_mode: | |
cur_request_id, next_request_id = next_request_id, cur_request_id | |
frame = next_frame | |
key = cv2.waitKey(1) | |
if key == 27: | |
break | |
if (9 == key): | |
is_async_mode = not is_async_mode | |
log.info("Switched to {} mode".format("async" if is_async_mode else | |
"sync")) | |
cv2.destroyAllWindows() | |
del exec_net | |
del plugin | |
if __name__ == '__main__': | |
sys.exit(main() or 0) |
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Thank you, it is very useful. I tried this with multiprocessing calls. the key==27: break doesn't seem to close the windows. any idea on why and whats the intended purpose of it, if its not exiting and destroying all windows.