에지클라우드_ 전처리 이미지 전송 모듈 작성

+import socket
+import cv2
+import numpy as np
+from queue import Queue
+from _thread import *
+enclose_q = Queue()
+import time
+def filter_img(img):
+    #이미지의 RGB값을 분석하여 찾는 실내 Tag가 맞는지 판별
+    img = cv2.resize(img, (10,10))
+    first = [0,0,0]
+    for x_loc in range(0, 10):
+        for y_loc in range(0, 10):
+            bgr_value = img[x_loc,y_loc]
+            first=first+bgr_value
+    first[0] = first[0]/100
+    first[1] = first[1]/100
+    first[2] = first[2]/100
+    blue = first[0]<200 and first[0]>120
+    green = first[1]>120 and first[1]<210
+    red = first[2]>130 and first[2]<230
+
+    if(blue and green and red):
+        return True
+    else:
+        return False
+
+def bboxes(inp):
+    #Frame을 인자로 전달받음
+    img = inp
+    start = time.time()
+    curTime = time.time()
+    # img2gray = cv2.imread(fname,0)
+    # img = cv2.namedWindow(img,cv2.WINDOW_NORMAL)
+    # img = cv2.resizeWindow(img,600,600)
+    img_final = inp
+    img2gray = cv2.cvtColor(inp, cv2.COLOR_BGR2GRAY) #GRAY Image 8bit per pixel
+    ret, mask = cv2.threshold(img2gray, 180, 255, cv2.THRESH_BINARY) #threshold : distinguish background, object
+    image_final = cv2.bitwise_and(img2gray, img2gray, mask=mask) #bitwise
+    ret, new_img = cv2.threshold(img_final, 180, 255, cv2.THRESH_BINARY)  # Nfor black text , cv.THRESH_BINARY_IV
+    newimg = cv2.cvtColor(new_img, cv2.COLOR_BGR2GRAY) #Gray Image converting
+    _,contours, _ = cv2.findContours(newimg, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)  # get contours
+    #cv2.CHAIN_APPROX_NONE: 모든 컨투어 포인트를 반환
+    for contour in contours:
+        [x, y, w, h] = cv2.boundingRect(contour)
+
+        if h / w > 1.0 or w / h > 2.0:
+            continue
+        #if h>40 or w>70:
+            #continue
+        if y>150:
+            continue
+        cropped = img_final[y :y +  h , x : x + w]
+        if(filter_img(cropped)):
+            cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 3)
+            cv2.putText(img,"cropped", (x-50,y-10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,255), 1)
+        else:
+            continue
+    return cropped
+
+def threaded(Client_socket, addr, queue):
+    print("Connected by : ", addr[0], " : ", addr[1])
+    while True:
+        try :
+            data = Client_socket.recv(1024)
+            if not data:
+                print("Disconnected")
+                break
+            StringData = queue.get()
+            Client_socket.send(str(len(StringData)).ljust(16).encode())
+            Client_socket.send(StringData)
+        except ConnectionResetError as e:
+            print("Disconnected")
+    Client_socket.close()
+
+
+def webcam(queue):
+    capture = cv2.VideoCapture(0)
+    while True:
+        ret, frame = capture.read()
+
+        if ret == False:
+            continue
+        frame = bboxes(frame)
+        encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 90]
+        result, imgencode = cv2.imencode('.jpg', frame, encode_param)
+        data = np.array(imgencode)
+        stringData = data.tostring()
+        queue.put(stringData)
+        cv2.imshow('image', frame)
+        key = cv2.waitKey(1)
+        if key == 27:
+            break
+
+if __name__ == '__main__':
+    HOST = '127.0.0.1'
+    PORT = 9999
+
+    server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    server_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+    server_socket.bind((HOST, PORT))
+    server_socket.listen()
+
+    print('server start')
+
+    start_new_thread(webcam, (enclose_q,))
+
+    while True:
+        print('wait')
+
+        client_socket, addr = server_socket.accept()
+        start_new_thread(threaded, (client_socket, addr, enclose_q,))
+    server_socket.close()