Commit f5f0447 · swadhin/aegisvision

Showing 28 changed files+1045-53

.gitignore backend/app/admin/__init__.py backend/app/admin/handelars.py backend/app/admin/pathtest.py backend/app/api/handelars.py backend/app/functions/encodeGenarator.py backend/app/functions/encodings.pickle backend/app/functions/face.py backend/app/functions/facedefine.py backend/app/functions/pictures/222156097.jpg backend/app/functions/pictures/222156116.jpg backend/app/functions/pictures/222156163.jpg backend/app/functions/pictures/222156259.jpeg backend/app/functions/pictures/222156288.jpeg backend/app/functions/pictures/222156469.png backend/app/functions/videoapp.py backend/app/models/studentmodel.py backend/app/routes/__init__.py backend/app/routes/routesadd.py backend/app/settings/connectdb.py backend/app/settings/example .env backend/funnytest.py backend/main.py cdn.html functionstest.py requirements.txt test2.py test3.py

▼.gitignore

+1-1

@@ -152,7 +152,7 @@ dmypy.json
152	152
153	153	# Cython debug symbols
154	154	cython_debug/
155		-
	155	+serviceAccountKey.json
156	156	# PyCharm
157	157	# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
158	158	# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
159	159

▼backend/app/api/__init__.py → backend/app/admin/__init__.py

+0-0

0

▼backend/app/admin/handelars.py

+93-0

@@ -0,0 +1,93 @@
	1	+from fastapi import Depends, HTTPException, status,UploadFile,File
	2	+from app.models.studentmodel import StudentModelshema
	3	+from fastapi import APIRouter
	4	+from app.settings.connectdb import Firebase
	5	+from typing import Dict,Any,Optional
	6	+from datetime import datetime
	7	+from app.functions.encodeGenarator import EndcodeGenarator
	8	+
	9	+
	10	+db_add=APIRouter()
	11	+db=Firebase()
	12	+imagepath=EndcodeGenarator().imagepath
	13	+picklepath=EndcodeGenarator().picklepath
	14	+
	15	+
	16	+@db_add.post("/create")
	17	+async def add_to_db(Student:StudentModelshema):
	18	+
	19	+ data={
	20	+ Student.id: {
	21	+ "name": Student.name,
	22	+ "email": Student.email,
	23	+ "status": Student.status,
	24	+ "Department": Student.Department,
	25	+ "Semester": Student.Semester,
	26	+ "Section": Student.Section,
	27	+ "Total_Attendance": Student.Total_Attendance,
	28	+ "last_seen": f"{datetime.now().strftime('%d-%m-%Y %H:%M:%S')}",
	29	+ }
	30	+ }
	31	+ x=db.set_data(data)
	32	+ return x
	33	+
	34	+@db_add.get("/getstudents")
	35	+async def get_from_db():
	36	+ data=db.get_data()
	37	+ return data
	38	+
	39	+@db_add.get("/getstudent/{id}")
	40	+async def get_from_db(id:str):
	41	+ data=db.get_data_by_key(id)
	42	+ return data
	43	+
	44	+@db_add.put("/updatestudent/{id}")
	45	+async def update_db(id:str,data:Dict[str,Any])->Dict[str,Any]:
	46	+ x=db.update_data(id,data)
	47	+ return x
	48	+
	49	+@db_add.delete("/deletestudent/{id}")
	50	+async def delete_from_db(id:str):
	51	+ x=db.delete_data(id)
	52	+ return x
	53	+
	54	+@db_add.get("/getstudentbydepartment/{department}")
	55	+async def get_from_db(department:str):
	56	+ data=db.get_data_by_child_value("Department",department)
	57	+ return data
	58	+@db_add.get("/getpresentstudents")
	59	+async def get_from_db():
	60	+ data=db.get_data_by_present()
	61	+ return data
	62	+@db_add.get("/getstudentbyrange/{start}/{end}")
	63	+async def get_from_db(start:int,end:int):
	64	+ data=db.get_data_by_child_range("Total_Attendance",start,end)
	65	+ return data
	66	+
	67	+@db_add.get("/getstudentbylimit/{limit}")
	68	+async def get_from_db(limit:int):
	69	+ data=db.get_data_by_child_limit("Total_Attendance",limit)
	70	+ return data
	71	+
	72	+@db_add.get("/uploadimage")
	73	+async def uploadimage(img:UploadFile=File(...)):
	74	+ try:
	75	+ content = await img.read()
	76	+ with open(imagepath, "wb") as file:
	77	+ file.write(content)
	78	+ return {"message":"Image uploaded"}
	79	+
	80	+ except Exception as e:
	81	+ return {"message":str(e)}
	82	+ finally:
	83	+ file.close()
	84	+@db_add.get("/encoding")
	85	+async def encoding():
	86	+ x=EndcodeGenarator().findencoding()
	87	+ return x
	88	+
	89	+
	90	+
	91	+
	92	+
	93	+
0	94

▼backend/app/admin/pathtest.py

+2-0

@@ -0,0 +1,2 @@
	1	+import os
	2	+
0	3

▼backend/app/api/handelars.py

+0-28

@@ -1,28 +0,0 @@
1		-from fastapi import Depends, HTTPException, status
2		-from app.models.studentmodel import StudentModel
3		-from fastapi import APIRouter
4		-from app.settings.connectdb import Firebase
5		-
6		-
7		-
8		-db_add=APIRouter()
9		-
10		-
11		-@db_add.post("/create")
12		-async def add_to_db(Student:StudentModel):
13		- ref=Firebase.ref
14		- data={
15		- Student.id: {
16		- "name": Student.name,
17		- "email": Student.email,
18		- "status": Student.status,
19		- "Department": Student.Department,
20		- "Semester": Student.Semester,
21		- "Section": Student.Section,
22		- "Total_Attendance": Student.Total_Attendance,
23		- "last_seen": Student.last_seen,
24		- }
25		- }
26		-
27		- ref.push(data)
28		- return {data:data}
29	0

▼backend/app/functions/encodeGenarator.py

+214-0

@@ -0,0 +1,214 @@
	1	+import os
	2	+import pickle
	3	+import face_recognition
	4	+import cv2
	5	+from app.settings.connectdb import Firebase
	6	+
	7	+
	8	+
	9	+
	10	+
	11	+
	12	+
	13	+class EndcodeGenarator:
	14	+ def __init__(self):
	15	+ self.known_face_encodings = []
	16	+ self.studentids = []
	17	+ self.encodings = []
	18	+ self.pathlist = os.listdir(os.path.join(os.path.dirname(__file__), "pictures"))
	19	+ self.picklepath = os.path.join(os.path.dirname(__file__), "encodings.pickle")
	20	+ self.imagepath = os.path.join(os.path.dirname(__file__), "pictures")
	21	+ self.ref = Firebase().ref
	22	+ self.bucket = Firebase().bucket
	23	+ self.idsref = Firebase().idsref
	24	+ imagepath=self.imagepath
	25	+ picklepath=self.picklepath
	26	+ pathlist=self.pathlist
	27	+
	28	+ def findencoding(self):
	29	+ imageList=self.pathlist
	30	+ for img in imageList:
	31	+ bucket=self.bucket
	32	+ ref=self.ref
	33	+ if not bucket.get_blob(f"faceappimage/{img}"):
	34	+ with open(f"{self.imagepath}/{img}","rb") as file:
	35	+ bucket.blob(f"faceappimage/{img}").upload_from_file(file)
	36	+ id=img.split(".")[0]
	37	+ self.studentids.append(id)
	38	+ if not ref.child(id).get():
	39	+ if img.endswith(".jpg") or img.endswith(".png") or img.endswith(".jpeg"):
	40	+ cv2img=cv2.imread(f"{self.imagepath}/{img}")
	41	+ img=cv2.cvtColor(cv2img,cv2.COLOR_BGR2RGB)
	42	+ encode=face_recognition.face_encodings(img)[0]
	43	+ self.encodings.append(encode)
	44	+ self.idsref.child(id).set(encode.tolist())
	45	+
	46	+
	47	+ encodeKnowlist=[self.encodings,self.studentids]
	48	+ file=open(self.picklepath,"wb")
	49	+ pickle.dump(encodeKnowlist,file)
	50	+ file.close()
	51	+
	52	+ return {
	53	+ "message":"encoding done",
	54	+ "status":"success",
	55	+ "data":"Knowlist saved in pickle file and Stored in firebase",
	56	+ }
	57	+
	58	+
	59	+
	60	+
	61	+
	62	+
	63	+
	64	+
	65	+
	66	+
	67	+
	68	+
	69	+
	70	+
	71	+
	72	+
	73	+# phots_path = os.path.join(os.path.dirname(__file__), "pictures")
	74	+
	75	+# pickle_path = os.path.join(os.path.dirname(__file__), "encodings.pickle")
	76	+
	77	+# pathlist = os.listdir(phots_path)
	78	+# print(pathlist)
	79	+
	80	+# print(phots_path)
	81	+
	82	+
	83	+
	84	+
	85	+# class EncodeGenarator:
	86	+ # def __init__(self):
	87	+ # self.known_face_encodings = []
	88	+ # self.known_face_names = []
	89	+ # self.path = os.path.join(os.path.dirname(__file__), "encodings.pickle")
	90	+ # self.load_encodings()
	91	+
	92	+ # def load_encodings(self):
	93	+ # if os.path.exists(self.path):
	94	+ # with open(self.path, "rb") as f:
	95	+ # self.known_face_encodings, self.known_face_names = pickle.load(f)
	96	+
	97	+ # def save_encodings(self):
	98	+ # with open(self.path, "wb") as f:
	99	+ # pickle.dump([self.known_face_encodings, self.known_face_names], f)
	100	+
	101	+ # def add_encoding(self, name: str, face_encoding: np.ndarray):
	102	+ # self.known_face_encodings.append(face_encoding)
	103	+ # self.known_face_names.append(name)
	104	+ # self.save_encodings()
	105	+
	106	+
	107	+
	108	+
	109	+
	110	+
	111	+
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	174	+
	175	+
	176	+
	177	+
	178	+ # def __init__(self):
	179	+ # self.known_face_encodings = []
	180	+ # self.known_face_names = []
	181	+ # self.path = os.path.join(os.path.dirname(__file__), "encodings.pickle")
	182	+ # self.load_encodings()
	183	+
	184	+ # def load_encodings(self):
	185	+ # if os.path.exists(self.path):
	186	+ # with open(self.path, "rb") as f:
	187	+ # self.known_face_encodings, self.known_face_names = pickle.load(f)
	188	+
	189	+ # def save_encodings(self):
	190	+ # with open(self.path, "wb") as f:
	191	+ # pickle.dump([self.known_face_encodings, self.known_face_names], f)
	192	+
	193	+ # def add_encoding(self, name: str, face_encoding: np.ndarray):
	194	+ # self.known_face_encodings.append(face_encoding)
	195	+ # self.known_face_names.append(name)
	196	+ # self.save_encodings()
	197	+
	198	+ # def get_face_encodings(self, image: np.ndarray) -> Dict[str, Any]:
	199	+ # face_locations = face_recognition.face_locations(image)
	200	+ # face_encodings = face_recognition.face_encodings(image, face_locations)
	201	+ # face_names = []
	202	+ # for face_encoding in face_encodings:
	203	+ # matches = face_recognition.compare_faces(self.known_face_encodings, face_encoding, setting.TOLERANCE)
	204	+ # name = "Unknown"
	205	+ # if True in matches:
	206	+ # first_match_index = matches.index(True)
	207	+ # name = self.known_face_names[first_match_index]
	208	+ # face_names.append(name)
	209	+ # return {"face_locations": face_locations, "face_names": face_names}
	210	+
	211	+ # def get_face_encodings_from_image(self, image_path: str) -> Dict[str, Any]:
	212	+ # image = cv2.imread(image_path)
	213	+ # rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
	214	+ # return self.get_face_encodings(rgb_image)
0	215

▼backend/app/functions/encodings.pickle

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▼backend/app/functions/face.py

+58-0

@@ -0,0 +1,58 @@
	1	+import os
	2	+import pickle
	3	+import cv2
	4	+import numpy as np
	5	+
	6	+
	7	+from face_recognition import face_locations, face_encodings, compare_faces, face_distance
	8	+class Face:
	9	+ def __init__(self,frame):
	10	+ self.frame=frame
	11	+ self.ids=[]
	12	+ def facedefine(self):
	13	+ frame=self.frame
	14	+ filepath=os.path.join(os.path.dirname(__file__), "encodings.pickle")
	15	+ file = open(filepath, 'rb')
	16	+ encodeListKnownWithIds = pickle.load(file)
	17	+
	18	+ encodeListKnown, studentIds = encodeListKnownWithIds
	19	+ imgs=cv2.resize(frame,(0,0),None,0.25,0.25)
	20	+ imgs=cv2.cvtColor(imgs,cv2.COLOR_BGR2RGB)
	21	+ faceCurFrame=face_locations(imgs)
	22	+ encodeCurFrame=face_encodings(imgs,faceCurFrame)
	23	+ if faceCurFrame:
	24	+ for encodeFace,faceLoc in zip(encodeCurFrame,faceCurFrame):
	25	+ matches=compare_faces(encodeListKnown,encodeFace)
	26	+ faceDis=face_distance(encodeListKnown,encodeFace)
	27	+ matchIndex=np.argmin(faceDis)
	28	+ if matches[matchIndex]:
	29	+ x=matches[matchIndex]
	30	+ y1,x2,y2,x1=faceLoc
	31	+ y1,x2,y2,x1=y14,x24,y24,x14
	32	+ bbox=55+x1,162+y1,x2-x1,y2-y1
	33	+ cv2.rectangle(frame,(x1,y1),(x2,y2),(0,255,0),2)
	34	+ cv2.rectangle(frame,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
	35	+ cv2.putText(frame,studentIds[matchIndex],(x1+6,y2-6),cv2.FONT_HERSHEY_COMPLEX,1,(255,255,255),2)
	36	+ self.ids.append(studentIds[matchIndex])
	37	+ print(self.ids)
	38	+
	39	+
	40	+ return frame
	41	+
	42	+
	43	+
	44	+
	45	+
	46	+
	47	+
	48	+
	49	+
	50	+
	51	+
	52	+
	53	+
	54	+
	55	+
	56	+
	57	+
	58	+
0	59

▼backend/app/functions/facedefine.py

+0-0

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▼backend/app/functions/pictures/222156097.jpg

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▼backend/app/functions/pictures/222156116.jpg

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▼backend/app/functions/pictures/222156163.jpg

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▼backend/app/functions/pictures/222156259.jpeg

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▼backend/app/functions/pictures/222156288.jpeg

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▼backend/app/functions/videoapp.py

+40-14

@@ -1,18 +1,44 @@
1	1	import cv2
2		-from app.settings import setting
	2	+import numpy as np
	3	+from fastapi import APIRouter
	4	+from fastapi.responses import StreamingResponse
	5	+from app.functions.face import Face
	6	+import streamlit as st
	7	+# from app.settings import setting
	8	+# camip=setting.CAM_IP
	9	+camip="192.168.0.100"
3	10
4		-class Camera:
5		- def __init__(self):
6		- self.cam = cv2.VideoCapture(f"http://{setting.CAM_IP}:{setting.CAM_PORT}/video")
	11	+
	12	+
	13	+videorouter = APIRouter()
	14	+
	15	+
	16	+
	17	+
	18	+def video_feed():
	19	+ cap = cv2.VideoCapture("http://"+camip+":8080/video")
	20	+ cap.set(3, 640)
	21	+ cap.set(4, 480)
	22	+
	23	+ while True:
	24	+ success, img = cap.read()
	25	+ x=Face(img)
	26	+ frame=x.facedefine()
	27	+ if not success:
	28	+ break
	29	+ ret, buffer = cv2.imencode('.jpg', frame)
7	30
8		- def get_frame(self):
9		- ret, frame = self.cam.read()
10		- if ret:
11		- ret, jpeg = cv2.imencode('.jpg', frame)
12		- return jpeg.tobytes()
13		- else:
14		- return None
15		-
16		- def __del__(self):
17		- self.cam.release()
	31	+ frame = buffer.tobytes()
	32	+ yield (b'--frame\r\n'
	33	+ b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
18	34
	35	+
	36	+
	37	+@videorouter.get("/video_feed")
	38	+def stream():
	39	+ return StreamingResponse(video_feed(), media_type="multipart/x-mixed-replace; boundary=frame")
	40	+def fetch():
	41	+ st.write("hello")
	42	+ return "hello"
	43	+
	44	+
19	45

▼backend/app/models/studentmodel.py

+1-2

@@ -1,6 +1,6 @@
1	1	from pydantic import BaseModel
2	2
3		-class StudentModel(BaseModel):
	3	+class StudentModelshema(BaseModel):
4	4	name: str
5	5	email: str
6	6	status: str
@@ -8,6 +8,5 @@ class StudentModel(BaseModel):
8	8	Semester: str
9	9	Section: str
10	10	Total_Attendance: str
11		- last_seen: str
12	11	id: str
13	12
14	13

▼backend/app/api/routes.py → backend/app/routes/__init__.py

+0-0

0

▼backend/app/routes/routesadd.py

+8-0

@@ -0,0 +1,8 @@
	1	+from fastapi import APIRouter
	2	+from app.admin.handelars import db_add
	3	+from app.functions.videoapp import videorouter
	4	+router = APIRouter()
	5	+
	6	+router.include_router(db_add, prefix="/admin", tags=["Admin"])
	7	+router.include_router(videorouter, prefix="/video", tags=["Video"])
	8	+
0	9

▼backend/app/settings/connectdb.py

+80-3

@@ -1,16 +1,93 @@
1	1	import firebase_admin
	2	+from typing import Dict,Any
2	3	from firebase_admin import credentials
3		-from firebase_admin import db
	4	+from firebase_admin import db,storage
	5	+import firebase_admin
4	6	import os
	7	+# from app.settings import setting
	8	+
5	9
6	10	class Firebase:
7		- path=os.path.join(os.path.dirname(__file__), "path/to/your/firebase/credentials.json")
	11	+
	12	+ firebase_url="https://database-faceapp-default-rtdb.asia-southeast1.firebasedatabase.app/"
	13	+ path=os.path.join(os.path.dirname(__file__), "serviceAccountKey.json")
8	14	cred = credentials.Certificate(path)
9	15	firebase_admin.initialize_app(cred,{
10		- 'databaseURL': 'https://database-faceapp-default-rtdb.asia-southeast1.firebasedatabase.app/'
	16	+ 'databaseURL': f'{firebase_url}',
	17	+ 'storageBucket': "database-faceapp.appspot.com"
11	18	})
12	19	ref=db.reference('students')
	20	+ idsref=db.reference('ids')
	21	+ bucket=storage.bucket()
	22	+
	23	+
	24	+ def get_data(self)->Dict[str,Any]:
	25	+ return self.ref.get()
	26	+
	27	+
	28	+ def set_data(self,data:Dict[str,Any])->Dict[str,Any]:
	29	+ for key,value in data.items():
	30	+ self.ref.child(key).set(value)
	31	+ return {"message":"Data Added Successfully",
	32	+ "data":data}
	33	+
	34	+
	35	+
	36	+ def update_data(self,key:str,data:Dict[str,Any])->Dict[str,Any]:
	37	+ self.ref.child(key).update(data)
	38	+ new_data=self.ref.child(key).get()
	39	+ return {
	40	+ "message":"Data Updated Successfully",
	41	+ "data":new_data
	42	+ }
	43	+
	44	+
	45	+ def delete_data(self,key:str)->Dict[str,Any]:
	46	+ self.ref.child(key).delete()
	47	+ return {"message":"Data Deleted Successfully"}
	48	+
	49	+ def get_data_by_key(self,key:str)->Dict[str,Any]:
	50	+ return self.ref.child(key).get()
	51	+
	52	+ def get_data_by_child(self,child:str)->Dict[str,Any]:
	53	+ return self.ref.order_by_child(child).get()
	54	+
	55	+ def get_data_by_child_value(self,child:str,value:str)->Dict[str,Any]:
	56	+ return self.ref.order_by_child(child).equal_to(value).get()
	57	+
	58	+ def get_data_by_child_range(self,child:str,start:int,end:int)->Dict[str,Any]:
	59	+ return self.ref.order_by_child(child).start_at(start).end_at(end).get()
	60	+
	61	+ def get_data_by_child_limit(self,child:str,limit:int)->Dict[str,Any]:
	62	+ return self.ref.order_by_child(child).limit_to_first(limit).get()
13	63
	64	+ def get_data_by_present(self)->Dict[str,Any]:
	65	+ return self.ref.order_by_child("status").equal_to("Present").get()
	66	+
	67	+
	68	+ def get_picture(self,img:str)->Dict[str,Any]:
	69	+ bucket=storage.bucket()
	70	+ return bucket.get_blob(f"faceappimage/{img}")
	71	+
	72	+
	73	+
	74	+
	75	+
	76	+
	77	+
	78	+
	79	+
	80	+
	81	+
	82	+
	83	+# # Example
	84	+# ref=db.reference('students')
	85	+# data=ref.get()
	86	+# print(data)
	87	+
	88	+# # Example
	89	+
	90	+# ref=db.reference('students')
14	91
15	92
16	93
17	94

▼backend/app/settings/example .env

+18-0

@@ -0,0 +1,18 @@
	1	+DATABASEURL=
	2	+SECRET_KEY=
	3	+HASH_KEY=
	4	+ALGROTHIM=
	5	+FIREBASE_API_KEY=
	6	+FIREBASE_AUTH_DOMAIN=
	7	+FIREBASE_DATABASE_URL=
	8	+FIREBASE_PROJECT_ID=
	9	+FIREBASE_STORAGE_BUCKET=
	10	+FIREBASE_MESSAGING_SENDER_ID=
	11	+FIREBASE_APP_ID=
	12	+FIREBASE_MEASUREMENT_ID=
	13	+CAMERA_ID=
	14	+CAM_IP=
	15	+CAM_PORT=
	16	+CAM_USER=
	17	+CAM_PASS=
	18	+
0	19

▼backend/funnytest.py

+13-0

@@ -0,0 +1,13 @@
	1	+import os
	2	+
	3	+
	4	+filepath=os.listdir("/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures")
	5	+ids=[]
	6	+for file in filepath:
	7	+
	8	+ id=file.split(".")[0]
	9	+ ids.append(id)
	10	+
	11	+
	12	+print(ids)
	13	+
0	14

▼backend/main.py

+8-3

@@ -1,10 +1,15 @@
1		-from app.functions.videoapp import Camera
2		-from fastapi import FastAPI, Response
3		-from app.models.studentmodel import StudentModel
	1	+
	2	+
	3	+from fastapi import FastAPI, APIRouter
	4	+from app.routes.routesadd import router
	5	+
	6	+# from app.models.studentmodel import StudentModel
4	7	from app.settings.connectdb import Firebase
5	8
6	9	app=FastAPI()
7	10
	11	+app.include_router(router)
	12	+
8	13
9	14	@app.get("/")
10	15	async def home():
11	16

▼cdn.html

+15-2

@@ -1,3 +1,16 @@
1	1
2		-<img src="https://demos.pixinvent.com/vuexy-nextjs-admin-template/demo-1/images/illustrations/auth/v2-login-light.png" alt="login" class="img-fluid" width="400" height="300" />
3		-<img src="https://demos.pixinvent.com/vuexy-nextjs-admin-template/demo-1/images/pages/auth-mask-light.png"/>
	2	+<!-- <img src="https://demos.pixinvent.com/vuexy-nextjs-admin-template/demo-1/images/illustrations/auth/v2-login-light.png" alt="login" class="img-fluid" width="400" height="300" />
	3	+<img src="https://demos.pixinvent.com/vuexy-nextjs-admin-template/demo-1/images/pages/auth-mask-light.png"/> -->
	4	+
	5	+<html>
	6	+ <head>
	7	+ <title>CDN</title>
	8	+ </head>
	9	+ <body>
	10	+ <h1>CDN</h1>
	11	+ <p>CDN is a content delivery network that helps to load the website faster.</p>
	12	+
	13	+ <video width="320" height="240">
	14	+ <source src="http://127.0.0.1:8000/video_feed"/>
	15	+ Your browser does not support the video tag.
	16	+ </body>
4	17

▼functionstest.py

+304-0

@@ -0,0 +1,304 @@
	1	+# import os
	2	+# import cv2
	3	+# import face_recognition
	4	+# from firebase_admin import credentials
	5	+# from firebase_admin import db,storage
	6	+# import firebase_admin
	7	+
	8	+
	9	+# image_dir=os.listdir("/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures")
	10	+
	11	+
	12	+# from firebase_admin import credentials
	13	+# from firebase_admin import db
	14	+
	15	+
	16	+# imagepath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures"
	17	+
	18	+# firbaseurl="https://database-faceapp-default-rtdb.asia-southeast1.firebasedatabase.app/"
	19	+# servicekey="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/settings/serviceAccountKey.json"
	20	+
	21	+
	22	+# cred=credentials.Certificate(servicekey)
	23	+
	24	+# firebase_admin.initialize_app(cred,{
	25	+# 'databaseURL': f'{firbaseurl}',
	26	+# 'storageBucket': 'database-faceapp.appspot.com',
	27	+# })
	28	+# # imagelist=os.listdir(imagepath)
	29	+# # print(imagelist)
	30	+# # buket=storage.bucket()
	31	+
	32	+# # for img in imagelist:
	33	+# # images=buket.get_blob(f"faceappimage/{img}")
	34	+# # print(img)
	35	+# # if not images:
	36	+# # with open(f"{imagepath}/{img}","rb") as file:
	37	+# # buket.blob(f"faceappimage/{img}").upload_from_file(file)
	38	+
	39	+# # x=buket.list_blobs()
	40	+# # print(x)
	41	+
	42	+# # ref=db.reference('ids')
	43	+
	44	+# # x=ref.get()
	45	+# # print(x)
	46	+
	47	+# # imageList=os.listdir(imagepath)
	48	+
	49	+
	50	+
	51	+# # for img in imageList:
	52	+
	53	+# # id=img.split(".")[0]
	54	+# # if not ref.child(id).get():
	55	+# # if img.endswith(".jpg") or img.endswith(".png") or img.endswith(".jpeg"):
	56	+# # cv2img=cv2.imread(f"{imagepath}/{img}")
	57	+# # img=cv2.cvtColor(cv2img,cv2.COLOR_BGR2RGB)
	58	+# # encode=face_recognition.face_encodings(img)[0]
	59	+# # ref.child(id).set(encode.tolist())
	60	+
	61	+
	62	+
	63	+
	64	+
	65	+
	66	+# # test={
	67	+# # "img1":"swadhin",
	68	+# # "img2":"swadhin",
	69	+# # "img3":"swadhin",
	70	+# # "img4":"swadhin",
	71	+# # "img5":"swadhin",
	72	+# # }
	73	+
	74	+# # x=test.keys()
	75	+# # for i in x:
	76	+# # print(i)
	77	+
	78	+
	79	+# # ids=['1','2','3','4','5','6','7','8','9','10']
	80	+
	81	+# # id=[[1],[23],[4],5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
	82	+# # known_face_encodings = [ids,id]
	83	+
	84	+# # print(known_face_encodings)
	85	+
	86	+
	87	+# imageList=os.listdir(imagepath)
	88	+# for img in imageList:
	89	+# bucket=storage.bucket()
	90	+# if not bucket.get_blob(f"faceappimage/{img}"):
	91	+# with open(f"{imagepath}/{img}","rb") as file:
	92	+# x=bucket.blob(f"faceappimage/{img}").upload_from_file(file)
	93	+# print(x)
	94	+
	95	+
	96	+# import os
	97	+# import pickle
	98	+# import face_recognition
	99	+# import cv2
	100	+# import numpy as np
	101	+# import cvzone
	102	+# from typing import Dict,Any
	103	+
	104	+
	105	+
	106	+
	107	+# cap=cv2.VideoCapture(0)
	108	+
	109	+# cap.set(3,640)
	110	+# cap.set(4,480)
	111	+# cap.set(10,100)
	112	+
	113	+# while True:
	114	+# _,img=cap.read()
	115	+# cv2.imshow("FaceApp",img)
	116	+# if cv2.waitKey(1) & 0xFF==ord('q'):
	117	+# break
	118	+# cap.release()
	119	+
	120	+# cv2.destroyAllWindows()
	121	+
	122	+
	123	+
	124	+# import cv2
	125	+# import time
	126	+# import uvicorn
	127	+# from fastapi import FastAPI, Request,WebSocket, WebSocketDisconnect
	128	+# from fastapi.templating import Jinja2Templates
	129	+# from fastapi.responses import StreamingResponse
	130	+
	131	+
	132	+
	133	+
	134	+
	135	+
	136	+# from fastapi import FastAPI, StreamingResponse
	137	+
	138	+
	139	+# app = FastAPI()
	140	+
	141	+# def generate_frames(cap):
	142	+# while True:
	143	+# success, frame = cap.read()
	144	+# if not success:
	145	+# break
	146	+# ret, buffer = cv2.imencode('.jpg', frame)
	147	+# frame = buffer.tobytes()
	148	+# yield (b'--frame\r\n'
	149	+# b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
	150	+
	151	+# @app.get("/video_feed")
	152	+# async def video_feed():
	153	+# cap = cv2.VideoCapture("https://192.168.0.103:3030/video") # 0 for default webcam
	154	+# return StreamingResponse(generate_frames(cap), media_type="multipart/x-mixed-replace;boundary=frame")
	155	+
	156	+# if __name__ == '__main__':
	157	+# uvicorn.run(app, host='127.0.0.1', port=8000)
	158	+
	159	+
	160	+# app=FastAPI()
	161	+
	162	+# face_cascade=cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
	163	+
	164	+# async def get_frame():
	165	+# camera=cv2.VideoCapture("https://192.168.0.103:3030/video")
	166	+# while True:
	167	+# success,frame=camera.read()
	168	+# if not success:
	169	+# break
	170	+# else:
	171	+# ret,buffer=cv2.imencode('.jpg',frame)
	172	+# frame=buffer.tobytes()
	173	+# yield(b'--frame\r\n'
	174	+# b'Content-Type: image/jpeg\r\n\r\n'+frame+b'\r\n')
	175	+# time.sleep(0.01)
	176	+
	177	+# @app.get('/')
	178	+# async def index():
	179	+
	180	+# return StreamingResponse(get_frame(),media_type='multipart/x-mixed-replace; boundary=frame')
	181	+
	182	+
	183	+# from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
	184	+# from fastapi.responses import HTMLResponse
	185	+# from websockets.exceptions import ConnectionClosed
	186	+# from fastapi.templating import Jinja2Templates
	187	+# import uvicorn
	188	+# import asyncio
	189	+# import cv2
	190	+
	191	+
	192	+# app = FastAPI()
	193	+# camera = cv2.VideoCapture(0,cv2.CAP_DSHOW)
	194	+
	195	+
	196	+
	197	+# @app.get('/')
	198	+# def index(request: Request):
	199	+
	200	+# return HTMLResponse("""
	201	+# <!DOCTYPE html>
	202	+# <html>
	203	+# <head>
	204	+# <title>Live Streaming</title>
	205	+# </head>
	206	+# <body>
	207	+# <img id="frame" src="">
	208	+# <script>
	209	+# let ws = new WebSocket("ws://localhost:8000/ws");
	210	+# let image = document.getElementById("frame");
	211	+# image.onload = function(){
	212	+# URL.revokeObjectURL(this.src); // release the blob URL once the image is loaded
	213	+# }
	214	+# ws.onmessage = function(event) {
	215	+# image.src = URL.createObjectURL(event.data);
	216	+# };
	217	+# </script>
	218	+# </body>
	219	+# </html>
	220	+
	221	+# """)
	222	+
	223	+
	224	+# @app.websocket("/ws")
	225	+# async def get_stream(websocket: WebSocket):
	226	+# await websocket.accept()
	227	+# try:
	228	+# while True:
	229	+# success, frame = camera.read()
	230	+# if not success:
	231	+# break
	232	+# else:
	233	+# ret, buffer = cv2.imencode('.jpg', frame)
	234	+# await websocket.send_bytes(buffer.tobytes())
	235	+# await asyncio.sleep(0.03)
	236	+# except (WebSocketDisconnect, ConnectionClosed):
	237	+# print("Client disconnected")
	238	+
	239	+
	240	+# if __name__ == '__main__':
	241	+# uvicorn.run(app, host='127.0.0.1', port=8000)
	242	+
	243	+
	244	+# img=cv2.cvtColor(cv2img,cv2.COLOR_BGR2RGB)
	245	+# encode=face_recognition.face_encodings(img)[0]
	246	+# encodeListknown=[encode,'222156259']
	247	+# success, frame = cap.read()
	248	+# imagesmall=cv2.resize(frame,(0,0),None,0.25,0.25)
	249	+# imagesmall=cv2.cvtColor(imagesmall,cv2.COLOR_BGR2RGB)
	250	+# facesCurFrame=face_recognition.face_locations(imagesmall)
	251	+# encodecurrentframe=face_recognition.face_encodings(imagesmall,facesCurFrame)
	252	+# if facesCurFrame:
	253	+# for encodeface,faceloc in zip(encodecurrentframe,facesCurFrame):
	254	+# matches=face_recognition.compare_faces(encodeListknown,encodeface)
	255	+# facedis=face_recognition.face_distance(encodeListknown,encodeface)
	256	+# matchindex=np.argmin(facedis)
	257	+# if matches[matchindex]:
	258	+# name="Swadhin"
	259	+# y1,x2,y2,x1=faceloc
	260	+# y1,x2,y2,x1=y14,x24,y24,x14
	261	+# cv2.rectangle(frame,(x1,y1),(x2,y2),(0,255,0),2)
	262	+# cv2.rectangle(frame,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
	263	+# cv2.putText(frame,name,(x1+6,y2-6),cv2.FONT_HERSHEY_COMPLEX,1,(255,255,255),2)
	264	+
	265	+
	266	+import cv2
	267	+import numpy as np
	268	+from face_recognition import face_encodings, face_locations, compare_faces, face_distance
	269	+
	270	+
	271	+path="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"
	272	+img=cv2.resize(cv2.imread(path),(0,0),None,0.25,0.25)
	273	+encodex=face_encodings(img)[0]
	274	+
	275	+frame="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"
	276	+
	277	+def detect_and_recognize_face(frame,encode):
	278	+ # Convert frame to RGB for face recognition
	279	+ frame=cv2.imread(frame)
	280	+ cut_frame=cv2.resize(frame,(0,0),None,0.25,0.25)
	281	+ rgb_frame = cv2.cvtColor(cut_frame, cv2.COLOR_BGR2RGB)
	282	+ frameencode=face_encodings(rgb_frame)
	283	+
	284	+
	285	+
	286	+
	287	+ # Find all faces and their encodings
	288	+ face_locations_list = face_locations(rgb_frame)
	289	+ currentfaceencode = face_encodings(frameencode, face_locations_list)
	290	+
	291	+ if face_locations_list:
	292	+
	293	+ # Loop through each detected face
	294	+ for face_encoding, face_location in zip(currentfaceencode, face_locations_list):
	295	+ # Compare face encoding with encodings in database/pickle file
	296	+ matches = compare_faces(encode, face_encoding)
	297	+ facedistance=face_distance(encode,face_encoding)
	298	+
	299	+ matchindex=np.argmin(facedistance)
	300	+ print(matchindex)
	301	+
	302	+
	303	+
	304	+detect_and_recognize_face(frame,encodex)
0	305

▼requirements.txt

+2-0

@@ -0,0 +1,2 @@
	1	+cmake <=3.27.4
	2	+
0	3

▼test2.py

+121-0

@@ -0,0 +1,121 @@
	1	+
	2	+import cv2
	3	+import streamlit as st
	4	+from fastapi import FastAPI
	5	+import face_recognition
	6	+import numpy as np
	7	+import time
	8	+import os
	9	+from fastapi.responses import StreamingResponse
	10	+app = FastAPI()
	11	+from face_recognition import face_locations, face_encodings
	12	+from firebase_admin import db ,credentials
	13	+
	14	+import firebase_admin
	15	+
	16	+
	17	+imagepath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures"
	18	+piclepath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/encodings.pickle"
	19	+
	20	+firbaseurl="https://database-faceapp-default-rtdb.asia-southeast1.firebasedatabase.app/"
	21	+servicekey="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/settings/serviceAccountKey.json"
	22	+
	23	+
	24	+cred=credentials.Certificate(servicekey)
	25	+
	26	+firebase_admin.initialize_app(cred,{
	27	+ 'databaseURL': f'{firbaseurl}',
	28	+ 'storageBucket': 'database-faceapp.appspot.com',
	29	+})
	30	+
	31	+path="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"
	32	+img=cv2.imread(path)
	33	+encodex=face_encodings(img)[0]
	34	+print(encodex)
	35	+
	36	+@st.cache_resource
	37	+def get_cap():
	38	+ return 0
	39	+
	40	+def detect_and_recognize_face(frame,encode):
	41	+ # Convert frame to RGB for face recognition
	42	+
	43	+ cut_frame=cv2.resize(frame,(0,0),None,0.25,0.25)
	44	+ rgb_frame = cv2.cvtColor(cut_frame, cv2.COLOR_BGR2RGB)
	45	+ frameencode=face_encodings(rgb_frame)
	46	+
	47	+
	48	+
	49	+
	50	+ # Find all faces and their encodings
	51	+ face_locations_list = face_locations(rgb_frame)
	52	+ currentfaceencode = face_encodings(frameencode, face_locations_list)
	53	+
	54	+ if face_locations_list:
	55	+
	56	+ # Loop through each detected face
	57	+ for face_encoding, face_location in zip(currentfaceencode, face_locations_list):
	58	+ # Compare face encoding with encodings in database/pickle file
	59	+ matches = face_recognition.compare_faces(encode, face_encoding)
	60	+ facedistance=face_recognition.face_distance(encode,face_encoding)
	61	+ print(facedistance)
	62	+ name = "Unknown"
	63	+ matchindex=np.argmin(facedistance)
	64	+ print(matchindex)
	65	+
	66	+ # Draw rectangle and name around the face
	67	+ top, right, bottom, left = face_location
	68	+ cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
	69	+ cv2.putText(frame, name, (left + 6, top - 6), cv2.FONT_HERSHEY_DUPLEX, 0.8, (255, 255, 255), 1)
	70	+
	71	+ return frame
	72	+
	73	+def generate_frames():
	74	+ cap=cv2.VideoCapture("https://192.168.0.100:8080/video")
	75	+ cap.set(3,640)
	76	+ cap.set(4,480)
	77	+ while True:
	78	+
	79	+ success, frame = cap.read() # read the camera frame
	80	+
	81	+ frame=detect_and_recognize_face(frame,encode=encodex)
	82	+
	83	+ if not success:
	84	+ break
	85	+ ret, buffer = cv2.imencode('.jpg', frame)
	86	+ frame = buffer.tobytes()
	87	+ yield (b'--frame\r\n'
	88	+ b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
	89	+
	90	+ # save_image=cv2.imwrite(os.path.join(/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/screens)"test.jpg",x)
	91	+
	92	+
	93	+
	94	+
	95	+
	96	+
	97	+
	98	+
	99	+
	100	+
	101	+# def video_feed():
	102	+# cap = get_cap() # 0 for default webcam
	103	+# return StreamingResponse(generate_frames(cap), media_type="multipart/x-mixed-replace; boundary=frame")
	104	+
	105	+@app.get("/")
	106	+async def home():
	107	+ return {"message":"Welcome to the Live Attendance System"}
	108	+
	109	+
	110	+@app.get("/video_feed")
	111	+async def video_feed():
	112	+ return StreamingResponse(generate_frames(), media_type="multipart/x-mixed-replace;boundary=frame")
	113	+
	114	+def main():
	115	+ app.run()
	116	+
	117	+if __name__ == '__main__':
	118	+ import uvicorn
	119	+
	120	+ uvicorn.run(app, host="localhost", port=8000)
	121	+
0	122

▼test3.py

+67-0

@@ -0,0 +1,67 @@
	1	+import cv2
	2	+import time
	3	+import numpy as np
	4	+
	5	+import pickle
	6	+from face_recognition import face_locations, face_encodings, compare_faces, face_distance
	7	+
	8	+folderpath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"
	9	+
	10	+pic=cv2.imread(folderpath)
	11	+pic=cv2.resize(pic,(0,0),None,0.25,0.25)
	12	+encode=face_encodings(pic)[0]
	13	+studentIds = ['222156259']
	14	+encodelist=[]
	15	+encodelist.append(encode)
	16	+incodelistnown=[encodelist,studentIds]
	17	+file=open('EncodeFile.p','wb')
	18	+pickle.dump(incodelistnown,file)
	19	+file.close()
	20	+
	21	+
	22	+cap = cv2.VideoCapture("https://192.168.0.100:8080/video")
	23	+cap.set(3, 640)
	24	+cap.set(4, 480)
	25	+
	26	+file = open('EncodeFile.p', 'rb')
	27	+encodeListKnownWithIds = pickle.load(file)
	28	+
	29	+encodeListKnown, studentIds = encodeListKnownWithIds
	30	+
	31	+
	32	+while True:
	33	+ success, img = cap.read()
	34	+ imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
	35	+ imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
	36	+ faceCurFrame = face_locations(imgS)
	37	+ encodeCurFrame =face_encodings(imgS, faceCurFrame)
	38	+ if faceCurFrame:
	39	+ for encodeFace, faceLoc in zip(encodeCurFrame, faceCurFrame):
	40	+ matches = compare_faces(encodeListKnown, encodeFace)
	41	+ faceDis = face_distance(encodeListKnown, encodeFace)
	42	+ matchIndex = np.argmin(faceDis)
	43	+ if matches[matchIndex]:
	44	+ y1, x2, y2, x1 = faceLoc
	45	+ y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
	46	+ bbox = 55 + x1, 162 + y1, x2 - x1, y2 - y1
	47	+ cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
	48	+ cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
	49	+ cv2.putText(img, studentIds[matchIndex], (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
	50	+ cv2.imshow('Webcam', img)
	51	+ if cv2.waitKey(1) & 0xFF == ord('q'):
	52	+ break
	53	+cap.release()
	54	+
	55	+cv2.destroyAllWindows()
	56	+
	57	+
	58	+
	59	+
	60	+
	61	+
	62	+
	63	+
	64	+
	65	+
	66	+
	67	+
0	68

have to fix bug