def crowd_detection(threshold, layout):
# Class definition
counting = Counting()
display = Display()
frame_manipulation = FrameManipulation()
report = Report()
roi = Roi()
# Var definition
create_roi = False
frame_id = 0
interval = 30
is_box_active = False
pts = []
report_duration = 0
threshold_confident = 0.05
using_roi = False
video_cap = cv2.VideoCapture(video_path)
# Set Yolo
net = cv2.dnn.readNet(yolo_weight_path, yolo_cfg_path)
# Set CUDA usage
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)
# Yolo Definition
layer_names = net.getLayerNames()
output_layers = [
layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()
]
# Set window
window = sg.Window("Kontrol",
layout,
size=(300, 380),
resizable=False,
finalize=True)
# Read until video is completed
while video_cap.isOpened():
event, values = window.read(timeout=20)
ret, frame = video_cap.read()
frame_id += 1
if ret:
# Var definition
boxes = []
confidences = []
mask = np.zeros((frame.shape[0], frame.shape[1], 3), np.uint8)
mask2 = np.zeros((frame.shape[0], frame.shape[1], 3), np.uint8)
if using_roi:
points = np.array(pts, np.int32)
points = points.reshape((-1, 1, 2))
mask2 = cv2.fillPoly(mask.copy(), [points],
(255, 255, 255))
frame_roi = cv2.bitwise_and(mask2, frame)
frame_to_detect = frame_roi
else:
mask2[:] = (255, 255, 255)
frame_to_detect = frame
# Detection object
people = Detection.detection_object(net, output_layers, boxes,
confidences,
threshold_confident,
frame_to_detect)
# Draw object detected on mask
frame_manipulation.draw_object_detected(boxes, people, mask)
if using_roi:
mask = cv2.bitwise_and(mask2, mask)
# Crowd counting
percentage = counting.occupancy_counting(mask, mask2)
# Person counting
person_detected = counting.people_counting(people)
# Draw bounding box
if is_box_active:
frame_manipulation.draw_bounding_box(
boxes, confidences, people, frame)
# Define ROI
if create_roi:
using_roi = roi.define_roi(window, pts, frame, percentage,
person_detected, threshold)
create_roi = not create_roi
# Show FPS
display.show_fps(frame_id, frame)
# Display frame
display.display_frame(using_roi, pts, frame)
# Create report
report_duration = report.create_report(report_duration,
interval, image_path,
log_path, percentage,
threshold,
person_detected, frame)
# Window update
window["-THRESHOLD1-"].update(value=threshold)
window["-CROWD1-"].update(value=person_detected)
window["-OCCUPY1-"].update(value=percentage)
else:
break
# Display frame
if event == '-BOUND-':
is_box_active = not is_box_active
# Create ROI (hide button)
if event == '-CREATE-':
create_roi = not create_roi
if event == '-EXIT-':
break
video_cap.release()
cv2.destroyAllWindows()
import json
from report import Report
r = Report("myreport_templates")
r.jinja["section1"] = "<h1></h1>"
r.create_report()
