mirror of
https://github.com/beetlea/camera_search.git
synced 2025-02-12 08:31:53 +00:00
272 lines
6.3 KiB
Python
272 lines
6.3 KiB
Python
import numpy as np
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import cv2
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from keras.applications.resnet50 import ResNet50
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from keras.preprocessing import image
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from keras.applications.resnet50 import preprocess_input, decode_predictions
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from imageai.Detection import ObjectDetection
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import os
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import serial
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import time
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face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')
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detector = ObjectDetection()
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detector.setModelTypeAsYOLOv3()
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detector.setModelPath("yolo.h5")
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detector.loadModel(detection_speed="flash")
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sotni = int()
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ser = serial.Serial('/dev/ttyACM0', 115200, timeout=0.2)
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cap = cv2.VideoCapture(1)
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detect1 = int()
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str1 = [0,0,0,0]
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str1[0] = 0
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str1[2] = 0
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u = int()
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def search_face(frame):
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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y2 = 0
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y1 = 0
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# Loop through all the faces detected and determine whether or not they are in the database
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identities = []
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for (x, y, w, h) in faces:
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#x1 = x
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y1 = y
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#x2 = x+w
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y2 = h
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#frame = cv2.rectangle(frame,(x1, y1),(x2, y2),(255,0,0),2)
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return y2, y1
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def step():
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i = 1
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u = 0
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while i:
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while u!=1:
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u = ser.write( b'v')
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u=0
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ff=ser.read(1)
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print(1111)
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if ff==b'B':
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i=0
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def step_y():
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i = 1
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u = 0
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while i:
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while u!=1:
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u = ser.write( b'V')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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step_right = int(0)
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step_left = int(0)
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def rotate_x(left, right):
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center = (right - left)/2 + left
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u = 0
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if center < 320:
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i=1
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while i:
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while u!=1:
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u = ser.write( b'r')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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# print("right")
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if center > 320:
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i=1
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while i:
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while u!=1:
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u = ser.write( b'l')
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u=0
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ff=ser.read(1)
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print(1111)
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if ff==b'B':
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i=0
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#print("left")
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global step_right
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global step_left
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if center > 360:
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step_right = step_right + 1
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step_left = step_left - 1
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if step_left < 0:
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step_left = 0
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if step_right < 30:
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step()
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else: step_right = 30
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if (center < 250 and center != 0):
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step_right = step_right - 1
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step_left = step_left + 1
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if step_right < 0:
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step_right = 0
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if step_left < 30:
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step()
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else: step_left = 30
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def rotate_y(vniz, vverx):
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#if up == 0:
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#step_none()
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#else: step_y1(up)
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center = (vverx - vniz)/2 + vniz
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#center = 480 - vverx
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step_y1(center)
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step_vverx = int()
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step_vniz = int()
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repeat = int()
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def step_none():
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u = 0
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global step_vverx
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global step_vniz
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global repeat
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if (step_vverx != 41 and repeat == 0):
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i=1
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while i:
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while u!=1:
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u = ser.write( b'R')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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#print ("vverx")
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step_vverx = step_vverx + 1
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step_vniz = step_vniz - 1
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if step_vniz < 0:
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step_vniz = 0
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if step_vverx < 40:
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step_y()
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else:
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step_vverx = 40
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repeat = 1
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if (step_vniz != 41 and repeat == 1):
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i=1
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while i:
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while u!=1:
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u = ser.write( b'L')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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#print ("vniz")
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step_vverx = step_vverx - 1
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step_vniz = step_vniz + 1
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if step_vverx < 0:
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step_vverx = 0
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if step_vniz < 40:
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step_y()
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else:
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step_vniz = 40
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repeat = 0
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def step_y1(center):
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global step_vverx
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global step_vniz
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u = 0
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if center < 300:
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i=1
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while i:
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while u!=1:
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u = ser.write( b'L')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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if center > 300:
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i=1
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while i:
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while u!=1:
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u = ser.write( b'R')
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u=0
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ff=ser.read(1)
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#print(1111)
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if ff==b'B':
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i=0
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if (center < 280 and center != 480 and center != 0):
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step_vverx = step_vverx + 1
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step_vniz = step_vniz - 1
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if step_vniz < 0:
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step_vniz = 0
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if step_vverx < 100:
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step_y()
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else: step_vverx = 100
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if center > 340:
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step_vverx = step_vverx - 1
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step_vniz = step_vniz + 1
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if step_vverx < 0:
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step_vverx = 0
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if step_vniz < 100:
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step_y()
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else: step_vniz = 100
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print(center)
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h = 0
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y1 = 0
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while(True):
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# Capture frame-by-frame
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ret, frame = cap.read()
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while ret != True:
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ret, frame = cap.read()
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# Our operations on the frame come here
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n = 0
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detected_copy, detections = detector.detectObjectsFromImage(input_image=frame, input_type ="array", output_type = "array")
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for eachObject in detections:
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if eachObject["name"] == "person":
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str1 = eachObject["box_points"]
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str2= str(str1)
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n = 1
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for i in range(5):
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if str2[i] in [","]:
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detect1 = int(str2[1:i])
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#print(detect1)
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print (eachObject["box_points"])
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#cv2.imwrite("1.jpg", frame)
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#list of x1,y1,x2 and y2
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#img = cv2.imread("image2new.jpg")
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left = str1[0]
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right = str1[2]
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rotate_x(left, right)
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if n == 1:
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niz = str1[1]
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verx = str1[3]
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else:
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verx = 0
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niz = 0
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rotate_y(niz, verx)
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#step_none()
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#time.sleep(1)
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#print(step_vverx, step_vniz)
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cv2.imshow("gggg", frame)
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if cv2.waitKey(33) == ord('q'):
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break
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# When everything done, release the capture
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cap.release()
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cv2.destroyAllWindows()
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