From 4101cddee4b873e6f2d1e85fb0f35d2914580c65 Mon Sep 17 00:00:00 2001 From: Sookeyy-12 Date: Sat, 11 Jan 2025 22:29:33 +0530 Subject: [PATCH 1/3] test --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 752af81..0324a72 100644 --- a/README.md +++ b/README.md @@ -1 +1,3 @@ -# DoorAutoCompiled \ No newline at end of file +# DoorAutoCompiled + +test \ No newline at end of file From 73ce1a0f557c758e24b8fb5f021f3de62ab279c0 Mon Sep 17 00:00:00 2001 From: Sookeyy-12 Date: Sun, 12 Jan 2025 01:52:54 +0530 Subject: [PATCH 2/3] updated --- .gitignore | 4 +++ AntiSpoofing.py | 42 ++++++++++++++++++++++++++ FaceRecognition.py | 45 ++++++++++++++++++++++++++++ GeneratedEncodings.p | Bin 0 -> 1204 bytes encodeGenerator.py | 34 +++++++++++++++++++++ main.py | 70 +++++++++++++++++++++++++++++++++++++++++++ models/best.pt | Bin 0 -> 6224537 bytes reqs.txt | Bin 0 -> 5676 bytes requirements-win.txt | Bin 0 -> 348 bytes requirements.txt | Bin 0 -> 1824 bytes 10 files changed, 195 insertions(+) create mode 100644 .gitignore create mode 100644 AntiSpoofing.py create mode 100644 FaceRecognition.py create mode 100644 GeneratedEncodings.p create mode 100644 encodeGenerator.py create mode 100644 main.py create mode 100644 models/best.pt create mode 100644 reqs.txt create mode 100644 requirements-win.txt create mode 100644 requirements.txt diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..27ca1e4 --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ +dlib +venv +Faces/* +windows \ No newline at end of file diff --git a/AntiSpoofing.py b/AntiSpoofing.py new file mode 100644 index 0000000..3917d95 --- /dev/null +++ b/AntiSpoofing.py @@ -0,0 +1,42 @@ +from ultralytics import YOLO +import cv2 +import cvzone +import math +import time + +confidence = 0.9 + +cap = cv2.VideoCapture(0) # for webcam +cap.set(3, 640) +cap.set(4, 480) +# cap = cv2.VideoCapture("test.mp4") # for video file + +model = YOLO("models/best.pt") +model.overrides['verbose'] = False + +classNames = ["fake", "real"] + +while True: + success, img = cap.read() + results = model(img, stream=True) + for r in results: + boxes = r.boxes + for box in boxes: + # Confidence + conf = math.ceil((box.conf[0] * 100))/100 + # class name + if conf > confidence: + cls = int(box.cls[0]) + if classNames[cls] == "real": + print("Real") + else: + print("Spoof") + + cv2.imshow("Image", img) + key = cv2.waitKey(1) & 0xFF + + # Exit if 'q' key is pressed + if key == ord("q"): + break + +cv2.destroyAllWindows() \ No newline at end of file diff --git a/FaceRecognition.py b/FaceRecognition.py new file mode 100644 index 0000000..980f34a --- /dev/null +++ b/FaceRecognition.py @@ -0,0 +1,45 @@ +import cv2 +import os +import pickle +import face_recognition +import numpy as np +import cvzone + +cap = cv2.VideoCapture(0) +cap.set(3, 640) # Set width +cap.set(4, 480) # Set height + +# Load the Encoding File +print("Loading encodings...") +encodings = open("GeneratedEncodings.p", "rb") +encodingListKnownWithIDs = pickle.load(encodings) +encodings.close() +encodeListKnown, studentIDs = encodingListKnownWithIDs +print("Encodings loaded.") + +while True: + success, img = cap.read() + + imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25) + imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB) + + faceCurrentFrame = face_recognition.face_locations(imgS) + encodeCurrentFrame = face_recognition.face_encodings(imgS,faceCurrentFrame) + + for encodeFace, faceLocation in zip(encodeCurrentFrame, faceCurrentFrame): + matches = face_recognition.compare_faces(encodeListKnown, encodeFace) + faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace) + matchIndex = np.argmin(faceDistance) + if matches[matchIndex]: + print("Known Face Detected") + print(studentIDs[matchIndex]) + + + cv2.imshow("Face Attendance", img) + + # Wait for a key press to break the loop + if cv2.waitKey(1) & 0xFF == ord('q'): + break + +cap.release() +cv2.destroyAllWindows() \ No newline at end of file diff --git a/GeneratedEncodings.p b/GeneratedEncodings.p new file mode 100644 index 0000000000000000000000000000000000000000..ce5eeafa5c1a75a42ea713b8a67bfdf63d9d4fb6 GIT binary patch literal 1204 zcmXApTTBx{6ov;Wq6rTeqmpRM8jWH!1nR9Z#%_QZwG}TYzDT80=RdQvXQxYb)pv9R zuT17&Q0Q?Kc@wgoE_;H*Q{c|Exm-3c^T$|S_H1WiiQDDLcC#wxkHR4HM;9IrN2-{K z_*hCr7OP@qy zmKuZ4QRhr}fV{S@7kpA3kA1?j#TB4w&9Zw~cl>DwEgc)Y2js7dab5EBsRQc5#@GfR z>1ineil>A|)U9#ts3R8z6{v^A*GTU`7myYuapZJ6=G6V0o`4q3lL}B>kuM`h(*`j| zy#eGmO0R(?Pi=TUq*OD$H@k~KV*Bh+qo_xF8WOHOW K^O)@nOZX2CBavJH literal 0 HcmV?d00001 diff --git a/encodeGenerator.py b/encodeGenerator.py new file mode 100644 index 0000000..3f7605b --- /dev/null +++ b/encodeGenerator.py @@ -0,0 +1,34 @@ +import cv2 +import face_recognition +import pickle +import os + +### Importing the Faces +folderPath = "Faces" +pathList = os.listdir(folderPath) +imgList = [] +studentIDs = [] +for path in pathList: + imgList.append(cv2.imread(os.path.join(folderPath, path))) + studentIDs.append(os.path.splitext(path)[0]) + +### Encodings Generator ### +def findEncodings(imagesList): + encodeList = [] + for img in imagesList: + img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) + encode = face_recognition.face_encodings(img)[0] + encodeList.append(encode) + + return encodeList + +print("Encoding Started...") +encodeListKnown = findEncodings(imgList) +encodingListKnownWithIDs = (encodeListKnown, studentIDs) +print("Encoding Complete.") + +file = open("GeneratedEncodings.p", "wb") +pickle.dump(encodingListKnownWithIDs, file) +file.close() + +print("Encodings Saved.") \ No newline at end of file diff --git a/main.py b/main.py new file mode 100644 index 0000000..a5f91fc --- /dev/null +++ b/main.py @@ -0,0 +1,70 @@ +import cv2 +import pickle +import face_recognition +import numpy as np +import math +from ultralytics import YOLO + +# Initialize video capture +cap = cv2.VideoCapture(0) +cap.set(3, 640) # Set width +cap.set(4, 480) # Set height + +# Load the Encoding File +print("Loading encodings...") +encodings = open("GeneratedEncodings.p", "rb") +encodingListKnownWithIDs = pickle.load(encodings) +encodings.close() +encodeListKnown, studentIDs = encodingListKnownWithIDs +print("Encodings loaded.") + +# Load the anti-spoofing model +model = YOLO("models/best.pt") +model.overrides['verbose'] = False +classNames = ["fake", "real"] +confidence = 0.9 + +while True: + success, img = cap.read() + + # Anti-spoofing check + results = model(img, stream=True) + is_real = False + for r in results: + boxes = r.boxes + for box in boxes: + conf = math.ceil((box.conf[0] * 100))/100 + if conf > confidence: + cls = int(box.cls[0]) + if classNames[cls] == "real": + is_real = True + break + if is_real: + break + + if is_real: + # Face recognition + imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25) + imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB) + + faceCurrentFrame = face_recognition.face_locations(imgS) + encodeCurrentFrame = face_recognition.face_encodings(imgS, faceCurrentFrame) + + for encodeFace, faceLocation in zip(encodeCurrentFrame, faceCurrentFrame): + matches = face_recognition.compare_faces(encodeListKnown, encodeFace) + faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace) + matchIndex = np.argmin(faceDistance) + if matches[matchIndex]: + print("Known Face Detected") + print(studentIDs[matchIndex]) + else: + print("Spoofing Attempt Detected") + + cv2.imshow("Face Attendance", img) + + # Wait for a key press to break the loop + if cv2.waitKey(1) & 0xFF == ord('q'): + break + +cap.release() +cv2.destroyAllWindows() diff --git a/models/best.pt b/models/best.pt new file mode 100644 index 0000000000000000000000000000000000000000..f28cdc8e28fda7a127f6af5a3b7243a353fb48cc GIT binary patch literal 6224537 zcmb5X2VfLc_x>NcgpPt;QBjEnNkW-C@^b#`l{X-7 zYHf44-L&ekdgz>44SS62mv>Ox|5`gH6L~`>b-~MP=QP#SB|3~=h5sh?gn_TFnqD6^ 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install -r reqs.txt + ``` + This 100% works on windows, but might need calibration in linux. + +3. run the app + ```bash + python main.py + ``` \ No newline at end of file

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