### ch06 程式碼下載 ###
$ cd ~/Lab
$ wget https://max543.com/debugger/class/python02/PiCamera/Lab/code/ch06.zip
$ unzip ch06.zip



### ex6-1 ###

# Google MediaPipe 官方網址
https://mediapipe.dev/



### ex6-2 ###

# 從已安裝 opencv 的虛擬環境，複製出一個名為 mediapipe 的 Python 3 虛擬環境
$ cpvirtualenv opencv mediapipe

# 在樹莓派 4 安裝 MediaPipe
(mediapipe) $ pip install mediapipe-rpi4==0.8.4.0

# 在樹莓派 3 安裝 MediaPipe
(mediapipe) $ pip install mediapipe-rpi3==0.8.4.0



### ex6-3 (6-1.py) ###

import cv2
import mediapipe as mp

mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

face_detection = mp_face_detection.FaceDetection(min_detection_confidence = 0.5)

while cap.isOpened():
    ret, frame = cap.read()

    if ret:
        frame = cv2.resize(frame, (WIDTH, HEIGHT))
        frame = cv2.rotate(frame, rotateCode = 1)
        frame = cv2.flip(frame, 1)
        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        frame.flags.writeable = False
        results = face_detection.process(frame)
        frame.flags.writeable = True
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

        if results.detections:
            for detection in results.detections:
                mp_drawing.draw_detection(frame, detection)

        cv2.imshow("MediaPipe Face Detection", frame)

    if cv2.waitKey(1) == 27:
        break

cap.release()
cv2.destroyAllWindows()



### ex6-4 (6-2.py) ###

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_face_mesh = mp.solutions.face_mesh

drawing_spec = mp_drawing.DrawingSpec(thickness = 1, circle_radius = 1)

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

face_mesh = mp_face_mesh.FaceMesh(min_detection_confidence = 0.5, min_tracking_confidence = 0.5)

while cap.isOpened():
    ret, frame = cap.read()

    if ret:
        frame = cv2.resize(frame, (WIDTH, HEIGHT))
        frame = cv2.rotate(frame, rotateCode = 1)
        frame = cv2.flip(frame, 1)

        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        frame.flags.writeable = False
        results = face_mesh.process(frame)
        frame.flags.writeable = True
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

        if results.multi_face_landmarks:
            for face_landmarks in results.multi_face_landmarks:
                mp_drawing.draw_landmarks(image = frame,
                   landmark_list = face_landmarks,
                   connections = mp_face_mesh.FACE_CONNECTIONS,
                   landmark_drawing_spec = drawing_spec,
                   connection_drawing_spec = drawing_spec)

        cv2.imshow("MediaPipe FaceMesh", frame)

    if cv2.waitKey(1) == 27:
        break

cap.release()
cv2.destroyAllWindows()



### ex6-5 (6-3.py) ###

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

hands = mp_hands.Hands(min_detection_confidence = 0.5, min_tracking_confidence = 0.5)

while cap.isOpened():
    ret, frame = cap.read()

    if ret:
        frame = cv2.resize(frame, (WIDTH, HEIGHT))
        frame = cv2.rotate(frame, rotateCode = 1)
        frame = cv2.flip(frame, 1)

        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        frame.flags.writeable = False
        results = hands.process(frame)
        frame.flags.writeable = True
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

        if results.multi_hand_landmarks:
            for hand_landmarks in results.multi_hand_landmarks:
                mp_drawing.draw_landmarks(frame, hand_landmarks, 
                                          mp_hands.HAND_CONNECTIONS)

        cv2.imshow("MediaPipe Hands", frame)

    if cv2.waitKey(1) == 27:
        break
        
cap.release()
cv2.destroyAllWindows()



### ex6-6 (6-4.py) ###

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_pose = mp.solutions.pose

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

pose = mp_pose.Pose(min_detection_confidence = 0.5, min_tracking_confidence = 0.5)
                    
while cap.isOpened():
    ret, frame = cap.read()

    if ret:
        frame = cv2.resize(frame, (WIDTH, HEIGHT))
        frame = cv2.rotate(frame, rotateCode = 1)
        frame = cv2.flip(frame, 1)

        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        frame.flags.writeable = False
        results = pose.process(frame)
        frame.flags.writeable = True
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
        mp_drawing.draw_landmarks(frame,
            results.pose_landmarks,
            mp_pose.POSE_CONNECTIONS)
        cv2.imshow("MediaPipe Pose", frame)

    if cv2.waitKey(1) == 27:
        break

cap.release()
cv2.destroyAllWindows()



### ex6-7 ###

# 在 mediapipe 虛擬環境中，繼續安裝 CVZone
(mediapipe) $ pip install cvzone==1.5.2



### ex6-8 (6-5.py) ###

from cvzone.FaceDetectionModule import FaceDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = FaceDetector()

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1)
    img = cv2.flip(img, 1)

    img, bboxs = detector.findFaces(img)

    if bboxs:
        # bboxInfo - "id","bbox","score","center"
        center = bboxs[0]["center"]
        cv2.circle(img, center, 5, (255, 0, 255), cv2.FILLED)

    cv2.imshow("Image", img)
    if cv2.waitKey(1) == 27:
        break
        
cap.release()
cv2.destroyAllWindows()



### ex6-9 (6-6.py) ###

from cvzone.FaceMeshModule import FaceMeshDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = FaceMeshDetector(maxFaces = 2)

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1) 
    img = cv2.flip(img, 1)

    img, faces = detector.findFaceMesh(img)

    if faces:
        print(faces[0])

    cv2.imshow("Image", img)

    if cv2.waitKey(1) == 27:
        break
    
cap.release()
cv2.destroyAllWindows()



### ex6-10 (6-7.py) ###

from cvzone.HandTrackingModule import HandDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = HandDetector(detectionCon = 0.5, maxHands = 2)

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1)
    # img = cv2.flip(img, 1)
    
    hands, img = detector.findHands(img)

    if hands:
        # Hand 1
        hand1 = hands[0]
        lmList1 = hand1["lmList"]
        bbox1 = hand1["bbox"]
        centerPoint1 = hand1['center']
        handType1 = hand1["type"]
        fingers1 = detector.fingersUp(hand1)

        if len(hands) == 2:
            # Hand 2
            hand2 = hands[1]
            lmList2 = hand2["lmList"]
            bbox2 = hand2["bbox"]
            centerPoint2 = hand2['center']
            handType2 = hand2["type"]
            fingers2 = detector.fingersUp(hand2)
            length, info, img = detector.findDistance(lmList1[8], lmList2[8], img)
    cv2.imshow("Image", img)
    if cv2.waitKey(1) == 27:
        break
        
cap.release()
cv2.destroyAllWindows()



### ex6-11 (6-7a.py) ###

from cvzone.HandTrackingModule import HandDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = HandDetector(detectionCon = 0.5, maxHands = 1)

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1)
    # img = cv2.flip(img, 1)

    hands, img = detector.findHands(img)

    if hands:
        hand = hands[0]
        bbox = hand['bbox']        
        fingers = detector.fingersUp(hand)
        totalFingers = fingers.count(1)
        cv2.putText(img, f'Fingers:{totalFingers}', (bbox[0] + 50, bbox[1] - 30),
                    cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)

    cv2.imshow("Image", img)

    if cv2.waitKey(1) == 27:
        break
        
cap.release()
cv2.destroyAllWindows()



### ex6-12 (6-7b.py) ###

from cvzone.HandTrackingModule import HandDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = HandDetector(detectionCon = 0.5, maxHands = 2)

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1)
    # img = cv2.flip(img, 1)

    hands, img = detector.findHands(img)

    if hands:
        # Hand 1
        hand1 = hands[0]
        lmList1 = hand1["lmList"]
        bbox1 = hand1["bbox"]
        centerPoint1 = hand1['center']
        handType1 = hand1["type"]
        fingers1 = detector.fingersUp(hand1)        
        length, info, img = detector.findDistance(lmList1[8], lmList1[12], img)
        cv2.putText(img, f'Dist:{int(length)}', (bbox1[0] + 50, bbox1[1] - 30),
                    cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
        
        if len(hands) == 2:
            # Hand 2
            hand2 = hands[1]
            lmList2 = hand2["lmList"]
            bbox2 = hand2["bbox"]
            centerPoint2 = hand2['center']
            handType2 = hand2["type"]
            fingers2 = detector.fingersUp(hand2)
            length, info, img = detector.findDistance(lmList1[8], lmList2[8], img)
            cv2.putText(img, f'Dist:{int(length)}',(bbox2[0] + 50, bbox2[1] - 30),
                            cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)

    cv2.imshow("Image", img)

    if cv2.waitKey(1) == 27:
        break
        
cap.release()
cv2.destroyAllWindows()



### ex6-13 (6-8.py) ###

from cvzone.PoseModule import PoseDetector
import cv2

cap = cv2.VideoCapture(0)
ratio = cap.get(cv2.CAP_PROP_FRAME_WIDTH) / cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
WIDTH = 400
HEIGHT = int(WIDTH / ratio)

detector = PoseDetector()

while cap.isOpened():
    success, img = cap.read()
    img = cv2.resize(img, (WIDTH, HEIGHT)) 
    img = cv2.rotate(img, rotateCode = 1)
    img = cv2.flip(img, 1)

    img = detector.findPose(img)

    lmList, bboxInfo = detector.findPosition(img, bboxWithHands = False)

    if bboxInfo:
        center = bboxInfo["center"]
        cv2.circle(img, center, 5, (255, 0, 255), cv2.FILLED)

    cv2.imshow("Image", img)

    if cv2.waitKey(1) == 27:
        break
    
cap.release()
cv2.destroyAllWindows()



### ex6-14 ###

# 從已安裝 opencv 的虛擬環境，複製出一個名為 tflite 的 Python 3 虛擬環境
$ cpvirtualenv opencv tflite

# 查詢 CPU 類型
(tflite) $ uname -m

# 查詢 Python 版本
(tflite) $ python --version



### ex6-15 ###

# 下載指定 CPU 和 Python 版本的 Wheel 檔來安裝 TensorFlow Lite
https://github.com/google-coral/pycoral/releases/



### ex6-16 ###

# 透過指令下載檔案 (請注意：官網的網址可能會更改)
(tflite) $ wget https://github.com/google-coral/pycoral/releases/download/v2.0.0/tflite_runtime-2.5.0.post1-cp37-cp37m-linux_armv7l.whl

# 直接網路安裝
(tflite) $ pip install https://github.com/google-coral/pycoral/releases/download/v2.0.0/tflite_runtime-2.5.0.post1-cp37-cp37m-linux_armv7l.whl



### ex6-17 ###

# 取得 TensorFlow Lite 預訓練模型：MobileNet
https://tfhub.dev/tensorflow/lite-model/ssd_mobilenet_v1/1/metadata/2