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python_fullcode.py
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python_fullcode.py
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import cv2
import datetime
import numpy as np
import pandas as pd
import time
from ultralytics import YOLO
from tracker import*
from math import dist
import supervision as sv
import xlsxwriter as xs
model=YOLO('yolov8n.pt')
video_info = sv.VideoInfo.from_video_path('veh2.mp4')
thickness =sv.calculate_dynamic_line_thickness(resolution_wh = video_info.resolution_wh)
text_scale =sv.calculate_dynamic_text_scale(resolution_wh = video_info.resolution_wh)
bounding_box_annotator = sv.BoundingBoxAnnotator(thickness=thickness)
label_annotator = sv.LabelAnnotator(text_scale=text_scale, text_thickness=thickness)
byte_track = sv.ByteTrack(frame_rate=video_info.fps)
class ViewTransformer:
def __init__(self,source: np.ndarray, target:np.ndarray):
source = source.astype(np.float32)
target=target.astype(np.float32)
self.m=cv2.getPerspectiveTransform(source,target)
def transform_points(self,points:np.ndarray) -> np.ndarray:
reshaped_points= points.reshape(-1,1,2).astype(np.float32)
transform_points= cv2.perspectiveTransform(reshaped_points,self.m)
return transform_points.reshape(-1,2)
def getDistanceFromPointToLine(p1, p2, p3):
return abs(np.cross(p2 - p1, p3 - p1) / np.linalg.norm(p2 - p1))
def drawLine(event, x, y, flags, param):
# Mouse event handlers for drawing lines
global x1, y1, drawing, detectionLines
if event == cv2.EVENT_LBUTTONDOWN:
if not drawing: # Start drawing a line
x1, y1 = x, y
drawing = True
else: # Stop drawing a line
x2, y2 = x, y
detectionLines.append([x1, y1, x2, y2])
drawing = False
elif event == cv2.EVENT_RBUTTONDOWN:
# Delete right clicked line
for i in detectionLines:
p1 = np.array([i[0], i[1]])
p2 = np.array([i[2], i[3]])
p3 = np.array([x, y])
if i[0] < i[2]:
largerX = i[2]
smallerX = i[0]
else:
largerX = i[0]
smallerX = i[2]
# Distance between the detection line and the point right clicked
if getDistanceFromPointToLine(p1, p2, p3) < 10 and smallerX - 10 < x < largerX + 10:
detectionLines.remove(i)
def RGB(event, x, y, flags, param):
if event == cv2.EVENT_MOUSEMOVE :
colorsBGR = [x, y]
print(colorsBGR)
# cv2.namedWindow('RGB')
# cv2.setMouseCallback('RGB', RGB)
global x1, y1, drawing, detectionLines
cap=cv2.VideoCapture('veh2.mp4')
my_file = open("coco.txt", "r")
data = my_file.read()
class_list = data.split("\n")
#print(class_list)
x1 = 0
y1 = 0
drawing = False
detectionLines = []
count=0
# tracker=Tracker()
# speed = Speed()
# cy1=322
# cy2=368
offset=20
vh_down={}
vh_down_time={}
counter=[]
vh_count_down={}
vh_up={}
vh_up_time={}
counter1=[]
vh_count_up={}
ret,frame1 = cap.read()
# if not ret:
# break
if count == 0:
# User draws the detection lines on preferred lanes in the first frame
cv2.namedWindow("RGB")
cv2.setMouseCallback("RGB", drawLine)
while 1:
frameCopy1 = frame1.copy()
frameCopy1=cv2.resize(frameCopy1,(1020,500))
k = cv2.waitKey(1) & 0xFF
if k == 27 or k == 32 or k == 13:
cv2.destroyAllWindows() # Finish drawing lines by pressing enter, space or escape
lanesCount = [0] * len(detectionLines)
break
for l in detectionLines: # Plot existing lines
cv2.line(frameCopy1, (l[0], l[1]), (l[2], l[3]), (255, 203, 48), 6)
cv2.imshow("RGB", frameCopy1)
x001=detectionLines[0][0]
c0y1=detectionLines[0][1]
x002=detectionLines[0][2]
y002=detectionLines[0][3]
x003=detectionLines[1][0]
c0y2=detectionLines[1][1]
x004=detectionLines[1][2]
y004=detectionLines[1][3]
TARGET_WIDTH=20
TARGET_HEIGHT=30
TARGET=np.array(
[
[0,0],
[TARGET_WIDTH -1,0],
[TARGET_WIDTH-1,TARGET_HEIGHT-1],
[0,TARGET_HEIGHT-1],
]
)
SOURCE= np.array([[x001,c0y1],[x002, y002], [x003, c0y2] , [x004, y004]])
polygon_zone = sv.PolygonZone( SOURCE, frame_resolution_wh=video_info.resolution_wh, triggering_position = sv.Position.CENTER)
view_transformer= ViewTransformer(source=SOURCE,target=TARGET)
wbook=xs.Workbook('/home/raspproject/yolov8counting-trackingvehicles-main/transportdata.xlsx')
ws=wbook.add_worksheet("first_sheet")
ws.write(0,0,"Daaate")
ws.write(0,1,"class")
ws.write(0,2,"confidence")
ws.write(0,3,"x coordinate")
ws.write(0,4,"y coordinate")
ws.write(0,5,"pixel x1")
ws.write(0,6,"pixel y1")
ws.write(0,7,"pixel x2")
ws.write(0,8,"pixel y2")
ws.write(0,9,"tracking id")
file = open("data3.txt" ,"a")
# file.write("Time_stamp"+"\t"+"\t "+"Tracking_id" +"\t"+ "Vehicle_class" + "\t" +"Speed_of_the_Vehicle"+"\n")
row=1
while True:
ret,frame = cap.read()
if not ret:
break
# if count == 0:
# # User draws the detection lines on preferred lanes in the first frame
# cv2.namedWindow("RGB")
# cv2.setMouseCallback("RGB", drawLine)
# while 1:
# frameCopy = frame.copy()
# frameCopy=cv2.resize(frameCopy,(1020,500))
# k = cv2.waitKey(1) & 0xFF
# if k == 27 or k == 32 or k == 13:
# cv2.destroyAllWindows() # Finish drawing lines by pressing enter, space or escape
# lanesCount = [0] * len(detectionLines)
# break
# for l in detectionLines: # Plot existing lines
# cv2.line(frameCopy, (l[0], l[1]), (l[2], l[3]), (255, 203, 48), 6)
# cv2.imshow("RGB", frameCopy)
frame=cv2.resize(frame,(1020,500))
# for dl in detectionLines: # Plot all detection lines
# cv2.line(frame, (dl[0], dl[1]), (dl[2], dl[3]), (255, 203, 48), 6)
x01=detectionLines[0][0]
cy1=detectionLines[0][1]
x02=detectionLines[0][2]
y02=detectionLines[0][3]
x03=detectionLines[1][0]
cy2=detectionLines[1][1]
x04=detectionLines[1][2]
y04=detectionLines[1][3]
count += 1
if count % 1 != 0:
continue
results=model(frame)[0]
# print(results)
# a=results[0].boxes.data
# px=pd.DataFrame(a).astype("float")
# print(px)
# list=[]
#
# for index,row in px.iterrows():
# # print(row)
#
# x1=int(row[0])
# y1=int(row[1])
# x2=int(row[2])
# y2=int(row[3])
# d=int(row[5])
# c=class_list[d]
detections = sv.Detections.from_ultralytics(results)
detections = detections[polygon_zone.trigger(detections)]
detections= byte_track.update_with_detections(detections=detections)
print(detections)
points=[[]]
if(len(detections.xyxy) !=0):
points=detections.get_anchors_coordinates(anchor=sv.Position.CENTER)
points=view_transformer.transform_points(points=points).astype(int)
print(points)
labels= [
f"#{tracker_id}"
for tracker_id in detections.tracker_id
]
for class_id,xyxy, confidence,points, tracker_id in zip(detections.class_id, detections.xyxy, detections.confidence,points, detections.tracker_id):
class_name =str(class_list[class_id])
if class_name == 'car':
print(class_name + "\t" + str(confidence) + "\t" + str(xyxy[0]) + "\t" + str(xyxy[1]) + "\t" + str(xyxy[2]) + "\t" + str(xyxy[3])+ "\t" + str(tracker_id))
file.write(str(datetime.datetime.fromtimestamp(time.time()))+"\t"+class_name + "\t" +str(points[0])+"\t"+ str(points[1])+"\t"+str(confidence) + "\t" + str(round(xyxy[0],6)) + "\t" + str(round(xyxy[1],6)) + "\t" + str(round(xyxy[2],6)) + "\t" + str(round(xyxy[3],6))+ "\t" + str(tracker_id)+"\n")
ws.write(row,0,str(datetime.datetime.fromtimestamp(time.time())))
ws.write(row,1,str(class_name))
ws.write(row,2,str(confidence))
ws.write(row,3,str(points[0]))
ws.write(row,4,str(points[1]))
ws.write(row,5,str(round(xyxy[0],6)))
ws.write(row,6,str(round(xyxy[1],6)))
ws.write(row,7,str(round(xyxy[2],6)))
ws.write(row,8,str(round(xyxy[3],6)))
ws.write(row,9,str(tracker_id))
row=row+1
RGB=frame.copy()
RGB=sv.draw_polygon(RGB, polygon=SOURCE, color=sv.Color.RED)
RGB=bounding_box_annotator.annotate(scene=RGB, detections=detections)
RGB=label_annotator.annotate(scene=RGB, detections=detections, labels= labels)
# cv2.imshow("RGB",RGB)
# if cv2.waitKey(1)&0xFF==27:
# break
# cap.release()
# cv2.destroyAllWindows()
# if 'car' in c or 'bus' in c or 'truck' in c or 'motorcycle' in c:
# # check = str(c)
# list.append([x1,y1,x2,y2,str(c)])
# bbox_id=tracker.update(list)
#
#
# for bbox in bbox_id:
# x3,y3,x4,y4,id,check=bbox
# cx=int(x3+x4)//2
# cy=int(y3+y4)//2
#
# if cy1<(cy+offset) and cy1>(cy-offset):
# vh_down_time[id]=time.time()
# vh_down[id]=cy
# vh_count_down[id]=count
#
# if id in vh_down:
# if cy2<(cy+offset) and cy2>(cy-offset):
# elapsed_time=time.time() - vh_down_time[id]
# # cv2.circle(frame,(cx,cy),4,(0,0,255),-1)
# # cv2.putText(frame,str(id),(cx,cy),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
# if counter.count(id)==0:
# counter.append(id)
# distance = 10 # meters
# diff=count-vh_count_down[id]
# # speed.speed_color(diff)
# a_speed_ms = distance / (diff/30)
# a_speed_kh = a_speed_ms * 3.6
# times=time.time()
# file.write(str(datetime.datetime.fromtimestamp(times))+"\t"+str(id)+"\t "+ str(check) + "\t"+"\t" + str(int(a_speed_kh))+"(Going_down)"+"\n")
# print("Hello")
# # file_1.write(str(time.time()) + " " + str(id) + " " + str(c) + " " + str(a_speed_kh) + "\n")
# cv2.circle(frame,(cx,cy),4,(0,0,255),-1)
# cv2.putText(frame,str(id),(cx,cy),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
# cv2.putText(frame,str(int(a_speed_kh))+'Km/h',(x4,y4 ),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
#
#
# if cy2<(cy+offset) and cy2>(cy-offset):
# vh_up[id]=cy
# vh_up_time[id]=time.time()
# vh_count_up[id]=count
# if id in vh_up:
# if cy1<(cy+offset) and cy1>(cy-offset):
# cv2.circle(frame,(cx,cy),4,(0,0,255),-1)
# cv2.putText(frame,str(id),(cx,cy),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
# if counter1.count(id)==0:
# counter1.append(id)
# distance1 = 10 # meters
# diff1=count-vh_count_up[id]
# a_speed_ms1 = distance / (diff1/30)
# a_speed_kh1 = a_speed_ms * 3.6
# file.write(str(datetime.datetime.fromtimestamp(times))+"\t"+str(id)+"\t "+ str(check) + "\t"+"\t" + str(int(a_speed_kh1))+"(Going_up)"+"\n")
# cv2.circle(frame,(cx,cy),4,(0,0,255),-1)
# cv2.putText(frame,str(id),(cx,cy),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
# cv2.putText(frame,str(int(a_speed_kh1))+'Km/h',(x4,y4),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
#
#
cv2.line(RGB,(x01,cy1),(x02,y02),(255,255,255),1)
cv2.putText(RGB,('Line-1'),(x01,cy1),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
cv2.line(RGB,(x03,cy2),(x04,y04),(255,255,255),1)
cv2.putText(RGB,('Line-2'),(x03,cy2),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
d=len(counter)
cv2.putText(RGB,('Going_Down-')+str(d),(60,40),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
d1=len(counter1)
cv2.putText(RGB,('Going_Up-')+str(d1),(60,130),cv2.FONT_HERSHEY_COMPLEX,0.8,(0,255,255),2)
cv2.imshow("RGB", RGB)
if cv2.waitKey(1)&0xFF==27:
file.close()
wbook.close()
break
cap.release()
cv2.destroyAllWindows()