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plot.py
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plot.py
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'''
In this file are defined functions for drawing Bird Eye View of ROI, bounding boxes and distancing lines.
'''
'''
Questo file contiene le funzioni per il disegno della Vista a Volo d'Uccello della ROI e delle bounding boxes.
'''
# imports
import cv2
import numpy as np
import math
# Function to draw Bird Eye View for region of interest(ROI). Red or Green.
# Red: Risk
# Green: Safe
def bird_eye_view(frame, distances_mat, bottom_points, scale_w, scale_h, risk_count, rotation_matrix):
h = frame.shape[0]
w = frame.shape[1]
red = (0, 0, 255)
green = (0, 255, 0)
blank_image = cv2.warpPerspective(frame, rotation_matrix, (w, h))
warped_pts = []
r = []
g = []
y = []
for i in range(len(distances_mat)):
if distances_mat[i][2] == 0:
if (distances_mat[i][0] not in r) and (distances_mat[i][0] not in g) and (distances_mat[i][0] not in y):
r.append(distances_mat[i][0])
if (distances_mat[i][1] not in r) and (distances_mat[i][1] not in g) and (distances_mat[i][1] not in y):
r.append(distances_mat[i][1])
blank_image = cv2.line(blank_image, (int(distances_mat[i][0][0] * scale_w), int(distances_mat[i][0][1] * scale_h)), (int(distances_mat[i][1][0] * scale_w), int(distances_mat[i][1][1]* scale_h)), red, 1)
for i in range(len(distances_mat)):
if distances_mat[i][2] == 1:
if (distances_mat[i][0] not in r) and (distances_mat[i][0] not in g) and (distances_mat[i][0] not in y):
y.append(distances_mat[i][0])
if (distances_mat[i][1] not in r) and (distances_mat[i][1] not in g) and (distances_mat[i][1] not in y):
y.append(distances_mat[i][1])
blank_image = cv2.line(blank_image, (int(distances_mat[i][0][0] * scale_w), int(distances_mat[i][0][1] * scale_h)), (int(distances_mat[i][1][0] * scale_w), int(distances_mat[i][1][1]* scale_h)), yellow, 1)
for i in range(len(distances_mat)):
if distances_mat[i][2] == 2:
if (distances_mat[i][0] not in r) and (distances_mat[i][0] not in g) and (distances_mat[i][0] not in y):
g.append(distances_mat[i][0])
if (distances_mat[i][1] not in r) and (distances_mat[i][1] not in g) and (distances_mat[i][1] not in y):
g.append(distances_mat[i][1])
for i in bottom_points:
blank_image = cv2.circle(blank_image, (int(i[0] * scale_w), int(i[1] * scale_h)), 5, green, 5)
for i in r:
blank_image = cv2.circle(blank_image, (int(i[0] * scale_w), int(i[1] * scale_h)), 5, red, 5)
return blank_image
# Function to draw bounding boxes according to risk factor for humans in a frame and draw lines between
# boxes according to risk factor between two humans.
# Red: Risk
# Green: Safe
def social_distancing_view(frame, distances_mat, boxes, confidences, classIDs, risk_count):
red = (0, 0, 255)
green = (0, 255, 0)
for i in range(len(boxes)):
x,y,w,h = boxes[i][:]
#################################
name = str(i)
(sx,sy), baseline = cv2.getTextSize(name, cv2.FONT_HERSHEY_PLAIN, 0.75, 1)
frame = cv2.rectangle(frame, (x,y), (x+w, y+h+11), green, 1)
frame = cv2.putText(frame, name, (x,y+baseline+6), cv2.FONT_HERSHEY_PLAIN, 0.75, (0,0,0), lineType=cv2.LINE_AA)
frame = cv2.putText(frame, f'{confidences[i]:.0%}', (x,y+baseline+12+h), cv2.FONT_HERSHEY_PLAIN, 0.75, (0,0,0), lineType=cv2.LINE_AA)
################################
for i in range(len(distances_mat)):
per1 = distances_mat[i][0]
per2 = distances_mat[i][1]
closeness = distances_mat[i][2]
if closeness == 0:
x,y,w,h = per1[:]
frame = cv2.rectangle(frame, (x,y), (x+w, y+h+11), red, 1)
x1,y1,w1,h1 = per2[:]
frame = cv2.rectangle(frame, (x1,y1), (x1+w1, y1+h1+11), red, 1)
frame = cv2.line(frame, (int(x+w/2), int(y+h/2)), (int(x1+w1/2), int(y1+h1/2)),red, 1)
#Calculates distance between points - calcolo la distanza tra i due punti
dist = math.sqrt((int(x1+w1/2) - (int(x+w/2)))**2 + (int(y1+h1/2) - int(y+h/2))**2)
#Finds medium point in the line - trovo il punto medio della linea disegnata
x_m_point = (int(x+w/2) + int(x1+w1/2))/2
y_m_point = (int(x+w/2) + int(y+h/2))/2
#cv2.putText(frame, str(dist), (int(x_m_point), int(y_m_point)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (66, 221, 245), 1)
pad = np.full((140,frame.shape[1],3), [110, 110, 100], dtype=np.uint8)
cv2.putText(pad, "Bounding box shows the level of risk to the person.", (50, 30),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (100, 100, 0), 2)
cv2.putText(pad, "-- RISK : " + str(risk_count[0]) + " people", (50, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 1)
cv2.putText(pad, "-- SAFE : " + str(risk_count[2]) + " people", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 1)
frame = np.vstack((frame,pad))
return frame