first commit

README.md

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+ROB 464 P1 - Red Team 2020

camera_cal.py

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+import numpy as np
+import cv2 as cv
+import glob
+
+# termination criteria
+criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
+objp = np.zeros((6*7,3), np.float32)
+objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)
+# Arrays to store object points and image points from all the images.
+objpoints = [] # 3d point in real world space
+imgpoints = [] # 2d points in image plane.
+images = glob.glob('calibration/*.jpg')
+for fname in images:
+    img = cv.imread(fname)
+    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+    # Find the chess board corners
+    ret, corners = cv.findChessboardCorners(gray, (7,6), None)
+    # If found, add object points, image points (after refining them)
+    if ret == True:
+        objpoints.append(objp)
+        corners2 = cv.cornerSubPix(gray,corners, (11,11), (-1,-1), criteria)
+        print(corners2)
+        imgpoints.append(corners)
+        # Draw and display the corners
+        cv.drawChessboardCorners(img, (7,6), corners2, ret)
+        cv.imshow('img', img)
+        cv.waitKey(500)
+
+cv.destroyAllWindows()
+
+ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
+
+np.savez('calib.npz', mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)

webcam_qr.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Tue Oct 7 11:41:42 2018
+
+@author: Caihao.Cui
+"""
+from __future__ import print_function
+
+import pyzbar.pyzbar as pyzbar
+import numpy as np
+import cv2
+import time
+
+# get the webcam:  
+cap = cv2.VideoCapture(0)
+
+cap.set(3,1920)
+cap.set(4,1080)
+#160.0 x 120.0
+#176.0 x 144.0
+#320.0 x 240.0
+#352.0 x 288.0
+#640.0 x 480.0
+#1024.0 x 768.0
+#1280.0 x 1024.0
+time.sleep(2)
+
+def decode(im) : 
+    # Find barcodes and QR codes
+    decodedObjects = pyzbar.decode(im)
+    # Print results
+    for obj in decodedObjects:
+        print('Type : ', obj.type)
+        print('Data : ', obj.data,'\n')     
+    return decodedObjects
+
+
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+#diagnal
+#cal_x = [306, 364, 450, 610, 890]
+
+cal_x = np.array([212, 254, 312, 420, 622])
+cal_y = np.array([30, 25, 20, 15, 10])
+
+cal_xp = np.array([220, 506, 940, 1374, 1700])
+cal_yp = np.array([36, 13, 0, 13, 36])
+
+while(cap.isOpened()):
+    # Capture frame-by-frame
+    ret, frame = cap.read()
+    # Our operations on the frame come here
+    im = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    decodedObjects = decode(im)
+
+    for decodedObject in decodedObjects: 
+        points = decodedObject.polygon
+
+        # If the points do not form a quad, find convex hull
+        if len(points) > 4 : 
+          hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
+          hull = list(map(tuple, np.squeeze(hull)))
+        else : 
+          hull = points;
+
+        cx = (hull[0][0] + hull[2][0]) / 2
+        cy = (hull[0][1] + hull[2][1]) / 2
+        frame = cv2.circle(frame, (int(cx), int(cy)), 10, (0, 255, 255), thickness=5)
+        print(cx, cy)
+
+        # Number of points in the convex hull
+        n = len(hull)     
+        # Draw the convext hull
+        for j in range(0,n):
+          cv2.line(frame, hull[j], hull[ (j+1) % n], (255,0,0), 3)
+
+        x = decodedObject.rect.left
+        y = decodedObject.rect.top
+
+        #pdist = np.sqrt(decodedObject.rect.width**2 + decodedObject.rect.height**2)
+        pdist = decodedObject.rect.height 
+        print("height", pdist)
+
+        xc = decodedObject.rect.left + decodedObject.rect.width/2
+        cfac = np.interp(xc, cal_xp, cal_yp)
+        print("correction amount", cfac)
+
+        pdist -= cfac
+        print("corrected height", pdist)
+        print("x", xc)
+
+        rdist = np.interp(pdist, cal_x, cal_y)
+        print("actual distance", rdist, " cm")
+
+        print(x, y)
+
+        print('Type : ', decodedObject.type)
+        print('Data : ', decodedObject.data,'\n')
+
+        barCode = str(decodedObject.data)
+        cv2.putText(frame, barCode, (x, y), font, 1, (0,255,255), 2, cv2.LINE_AA)
+
+    # Display the resulting frame
+    frame = cv2.resize(frame, (640, 360))
+    cv2.imshow('frame',frame)
+    key = cv2.waitKey(1)
+    if key & 0xFF == ord('q'):
+        break
+    elif key & 0xFF == ord('s'): # wait for 's' key to save 
+        cv2.imwrite('Capture.png', frame)     
+
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()

webcam_qr_perspective.py

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+from __future__ import print_function
+
+import pyzbar.pyzbar as pyzbar
+import numpy as np
+import cv2
+import time
+import glob
+
+with np.load('calib.npz') as X:
+    mtx, dist, _, _ = [X[i] for i in ('mtx','dist','rvecs','tvecs')]
+objp = np.array([[1, 1, 0], [0, 1, 0], [0, 0, 0], [1, 0, 0]], dtype=np.float32)
+
+# get the webcam:  
+cap = cv2.VideoCapture(0)
+
+cap.set(3,1920)
+cap.set(4,1080)
+time.sleep(2)
+
+def decode(im) : 
+    # Find barcodes and QR codes
+    decodedObjects = pyzbar.decode(im)
+    # Print results
+    for obj in decodedObjects:
+        print('Type : ', obj.type)
+        print('Data : ', obj.data,'\n')     
+    return decodedObjects
+
+
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+while(cap.isOpened()):
+    # Capture frame-by-frame
+    ret, frame = cap.read()
+    # Our operations on the frame come here
+    im = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    decodedObjects = decode(im)
+
+    for decodedObject in decodedObjects: 
+        points = decodedObject.polygon
+
+        # If the points do not form a quad, find convex hull
+        if len(points) > 4 : 
+          hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
+          hull = list(map(tuple, np.squeeze(hull)))
+        else : 
+          hull = points;
+
+        # Number of points in the convex hull
+        n = len(hull)
+
+        if n == 4:
+            cx = (hull[0].x + hull[2].x) / 2
+            cy = (hull[0].y + hull[2].y) / 2
+            frame = cv2.circle(frame, (int(cx), int(cy)), 5, (0, 0, 0))
+            hull.sort(key=lambda p: np.arctan2(p.y - cy, p.x - cx)) #sort counterclockwise
+            print(hull)
+            ret, rvecs, tvecs = cv2.solvePnP(objp, np.array(hull, dtype=np.float64), mtx, dist)
+            print(tvecs)
+
+            # Draw the convext hull
+            for j in range(0,n):
+                cv2.line(frame, hull[j], hull[ (j+1) % n], (255,0,0), 3)
+            cv2.line(frame, hull[1], hull[2], (0,0,255), 3)
+
+        print('Type : ', decodedObject.type)
+        print('Data : ', decodedObject.data,'\n')
+
+        #barCode = str(decodedObject.data)
+       #cv2.putText(frame, barCode, (x, y), font, 1, (0,255,255), 2, cv2.LINE_AA)
+
+    # Display the resulting frame
+    frame = cv2.resize(frame, (640, 360))
+    cv2.imshow('frame',frame)
+    key = cv2.waitKey(1)
+    if key & 0xFF == ord('q'):
+        break
+    elif key & 0xFF == ord('s'): # wait for 's' key to save 
+        cv2.imwrite('Capture.png', frame)     
+
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()