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video_norm.py

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+import numpy as np
+import cv2
+
+from keras.applications.resnet50 import ResNet50
+from keras.preprocessing import image
+from keras.applications.resnet50 import preprocess_input, decode_predictions
+
+from imageai.Detection import ObjectDetection
+import os
+import serial
+import time
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')
+detector = ObjectDetection()
+detector.setModelTypeAsYOLOv3()
+detector.setModelPath("yolo.h5")
+detector.loadModel(detection_speed="flash")
+sotni = int()
+ser = serial.Serial('/dev/ttyACM0', 115200,  timeout=0.2)
+cap = cv2.VideoCapture(1)
+detect1 = int()
+str1 = [0,0,0,0]
+str1[0] = 0   
+str1[2] = 0 
+
+u = int()
+def search_face(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+    y2 = 0
+    y1 = 0
+    # Loop through all the faces detected and determine whether or not they are in the database
+    identities = []
+    for (x, y, w, h) in faces:
+        #x1 = x
+        y1 = y
+        #x2 = x+w
+        y2 = h
+
+        #frame = cv2.rectangle(frame,(x1, y1),(x2, y2),(255,0,0),2)
+    return y2, y1
+
+def step():
+    i = 1
+    u = 0
+    while i:
+        while u!=1:
+
+            u = ser.write( b'v') 
+        u=0 
+        ff=ser.read(1)
+        print(1111)
+        if ff==b'B':
+            i=0
+def step_y():
+    i = 1
+    u = 0
+    while i:
+        while u!=1:
+            u = ser.write( b'V') 
+        u=0 
+        ff=ser.read(1)
+        #print(1111)
+        if ff==b'B':
+            i=0
+step_right = int(0)
+step_left = int(0)
+def rotate_x(left, right):
+    center = (right - left)/2 + left
+    u = 0
+    if center < 320:
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'r') 
+            u=0 
+            ff=ser.read(1)
+            #print(1111)
+            if ff==b'B':
+                i=0
+       # print("right")
+    if center > 320:
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'l') 
+            u=0 
+            ff=ser.read(1)
+            print(1111)
+            if ff==b'B':
+               i=0
+        #print("left")
+    global step_right
+    global step_left
+    if center > 360:
+        
+        step_right = step_right + 1
+        step_left = step_left - 1
+        if step_left < 0:
+            step_left = 0
+        if step_right < 30:
+            step()
+        else: step_right = 30
+    if (center < 250 and center != 0):
+        step_right = step_right - 1
+        step_left = step_left + 1
+        if step_right < 0:
+            step_right = 0
+        if step_left < 30:
+            step()
+        else: step_left = 30
+
+def rotate_y(vniz, vverx):
+    #if up == 0:
+        #step_none()
+    #else: step_y1(up)
+    center = (vverx - vniz)/2 + vniz
+    #center = 480 - vverx
+    step_y1(center)
+
+step_vverx = int()
+step_vniz = int()
+repeat = int()
+
+
+def step_none():
+    u = 0
+    global step_vverx
+    global step_vniz
+    global repeat
+    if (step_vverx != 41 and repeat == 0):
+
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'R') 
+            u=0 
+            ff=ser.read(1)
+            #print(1111)
+            if ff==b'B':
+                i=0
+        #print ("vverx")
+
+        step_vverx = step_vverx + 1
+        step_vniz = step_vniz - 1
+        if step_vniz < 0:
+            step_vniz = 0
+        if step_vverx < 40:
+            step_y()
+        else: 
+            step_vverx = 40
+            repeat = 1
+
+    if (step_vniz != 41 and repeat == 1):
+
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'L') 
+            u=0 
+            ff=ser.read(1)
+            #print(1111)
+            if ff==b'B':
+                i=0
+        #print ("vniz")
+
+        step_vverx = step_vverx - 1
+        step_vniz = step_vniz + 1
+        if step_vverx < 0:
+            step_vverx = 0
+        if step_vniz < 40:
+            step_y()
+        else: 
+            step_vniz = 40
+            repeat = 0
+
+
+def step_y1(center):
+    global step_vverx
+    global step_vniz
+    u = 0
+    if center < 300:
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'L') 
+            u=0 
+            ff=ser.read(1)
+            #print(1111)
+            if ff==b'B':
+                i=0
+    if center > 300:
+        i=1
+        while i:
+            while u!=1:
+
+                u = ser.write( b'R') 
+            u=0 
+            ff=ser.read(1)
+            #print(1111)
+            if ff==b'B':
+                i=0
+    if (center < 280 and center != 480 and center != 0):
+
+        step_vverx = step_vverx + 1
+        step_vniz = step_vniz - 1
+        if step_vniz < 0:
+            step_vniz = 0
+        if step_vverx < 100:
+            step_y()
+        else: step_vverx = 100
+    if center > 340:
+
+        step_vverx = step_vverx - 1
+        step_vniz = step_vniz + 1
+        if step_vverx < 0:
+            step_vverx = 0
+        if step_vniz < 100:
+            step_y()
+        else: step_vniz = 100
+
+    print(center)
+h = 0
+y1 = 0
+while(True):
+# Capture frame-by-frame
+    ret, frame = cap.read()
+    while ret != True:
+        ret, frame = cap.read()
+# Our operations on the frame come here
+    n = 0
+    detected_copy, detections = detector.detectObjectsFromImage(input_image=frame, input_type ="array", output_type = "array")
+    for eachObject in detections:
+        if eachObject["name"] == "person":
+            str1 = eachObject["box_points"]
+            str2= str(str1)
+            n = 1
+            for i in range(5):
+                if str2[i] in [","]:
+                    detect1 = int(str2[1:i])
+                    #print(detect1)
+            print (eachObject["box_points"])
+    #cv2.imwrite("1.jpg", frame)
+
+#list of x1,y1,x2 and y2
+    #img = cv2.imread("image2new.jpg") 
+
+    left = str1[0]
+    right = str1[2]
+    rotate_x(left, right)
+    if n == 1:
+        niz = str1[1]
+        verx = str1[3]
+    else: 
+        verx = 0
+        niz = 0
+    rotate_y(niz, verx)
+    #step_none()
+
+
+    #time.sleep(1)
+    #print(step_vverx, step_vniz)
+    cv2.imshow("gggg", frame)
+    if cv2.waitKey(33) == ord('q'):
+        break
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()