defMTest.py
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# Hand Tracing Module
import cv2
import mediapipe as mp
import time
import base64
import requests
import json
import configparser
import ctypes
import sys
#from PIL import Image
#import io
#import numpy as np
class handDetector:
def __init__(self, mode=False, maxHands=2, detectionCon=0.5, trackCon=0.5):
self.mode = mode
self.maxHands = maxHands
self.detectionCon = detectionCon
self.trackCon = trackCon
self.mpHands = mp.solutions.hands
# self.hands = self.mpHands.Hands(self.mode, self.maxHands,self.detectionCon, self.trackCon)
self.hands = self.mpHands.Hands()
self.mpDraw = mp.solutions.drawing_utils
def findHands(self, img, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.results = self.hands.process(imgRGB)
# print(results.multi_hand_landmarks)
if self.results.multi_hand_landmarks:
for handLms in self.results.multi_hand_landmarks:
if draw:
self.mpDraw.draw_landmarks(img, handLms,
self.mpHands.HAND_CONNECTIONS)
return img
def findPosition(self, img, handNo=-1, draw=True):
lmList = []
if(handNo == -1):
if self.results.multi_hand_landmarks:
# myHand = self.results.multi_hand_landmarks[handNo]
for myHand in self.results.multi_hand_landmarks:
for id, lm in enumerate(myHand.landmark):
# print(id, lm)
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
# print(id, cx, cy)
lmList.append([id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 8, (255, 0, 255), cv2.FILLED)
else:
if self.results.multi_hand_landmarks:
myHand = self.results.multi_hand_landmarks[handNo]
for id, lm in enumerate(myHand.landmark):
# print(id, lm)
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
# print(id, cx, cy)
lmList.append([id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 8, (255, 0, 255), cv2.FILLED)
return lmList
def image_to_base64(self,img):
# 将图像转换为Base64字符串
_, img_encoded = cv2.imencode('.jpg', img)
base64_data = base64.b64encode(img_encoded)
return base64_data.decode("utf-8")
def base64_to_image(self, base64_string, save_path):
try:
# 解码Base64字符串为字节数据
image_data = base64.b64decode(base64_string)
# 将字节数据转换为numpy数组
np_array = np.frombuffer(image_data, np.uint8)
# 解码numpy数组为图像
image = cv2.imdecode(np_array, cv2.IMREAD_COLOR)
# 保存图像到指定路径
cv2.imwrite(save_path, image)
print(f"Image saved successfully at {save_path}")
return image
except Exception as e:
print(f"An error occurred during Base64 to image conversion: {str(e)}")
return None
# image_data = base64.b64decode(base64_string)
# image = Image.open(io.BytesIO(image_data))
# image.save(save_path)
# print(f"Image saved successfully at {save_path}")
# except Exception as e:
# print(f"An error occurred during Base64 to image conversion: {str(e)}")
def save_input_to_txt(self,input_str, file_path):
try:
with open(file_path, 'w', encoding='utf-8') as file:
file.write(input_str)
print("数据已成功保存到txt文件中。")
except Exception as e:
print(f"保存数据到txt文件时出错：{str(e)}")
def post_string_to_http_api(self,api_url,input_str, points):
try:
headers = {'Content-Type': 'application/json'}
json_str = json.dumps(points)
length=len(points)
data = {'input': input_str,"points":json_str,"pointLen":length}
# print(input_str)
response = requests.post(api_url, headers=headers, data=json.dumps(data))
if response.status_code == 200:
# 可根据需要处理响应结果
print(f"Request ok:{response.status_code}")
# response_data = response.json()
# return response_data
return response.text
else:
# 处理请求错误
print(f"Request failed with status code {response.status_code}")
return None
except requests.exceptions.RequestException as e:
# 处理连接错误等请求异常
print(f"An error occurred during the request: {str(e)}")
return None
except Exception as e:
# 处理其他异常
print(f"An error occurred: {str(e)}")
return None
def readConfig(self):
try:
# 创建一个 ConfigParser 对象
config = configparser.ConfigParser()
# 读取配置文件
config.read('config.ini')
# 获取相机索引号和配置的接口地址
camera_index = int(config.get('Camera', 'index'))
api_url = config.get('API', 'url')
# 打印获取到的值
print(f"Camera Index: {camera_index}")
print(f"API URL: {api_url}")
return [camera_index, api_url]
except Exception as e:
# 处理其他异常
print(f"readconfig error: {str(e)}")
return [0,"http://localhost:8765"]
def is_admin():
try:
return ctypes.windll.shell32.IsUserAnAdmin()
except:
return False
def main():
if(is_admin()==False):
print("not admin , need run as admin")
ctypes.windll.shell32.ShellExecuteW(None,"runas", sys.executable, __file__, None, 1)
return
input_str=""
# api_url="http://localhost:8765/rest/api/v1/imgUpload"
# camera_index=0
detector = handDetector()
configResult=detector.readConfig()
camera_index=configResult[0]
api_url=configResult[1]+"/rest/api/v1/imgUpload"
# pTime = 0
# cTime = 0
cap = cv2.VideoCapture(camera_index)
detector.__init__(False,2,0.5,0.5)
while True:
success, img = cap.read()
if(success):
img = detector.findHands(img)
lmList = detector.findPosition(img)
# if len(lmList) != 0:
# print(lmList[4])
# cTime = time.time()
# fps = 1 / (cTime - pTime)
# pTime = cTime
# cv2.imwrite("1.jpg",img)
# cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3,(255, 0, 255), 3)
input_str=detector.image_to_base64(img)
# detector.save_input_to_txt(input_str, "input.txt")
# detector.base64_to_image(input_str,"input.jpg")
detector.post_string_to_http_api(api_url,input_str,lmList)
# cv2.imshow("Image", img)
# cv2.waitKey(1)
else:
print("camera read error")
break
time.sleep(0.2)
if __name__ == "__main__":
main()