This is the proper working code of final year project commit 1

Author: kattianirudh

000.jpg

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+import matplotlib.pyplot as plt
+import matplotlib.gridspec as gridspec
+import cv2
+
+import numpy as np
+
+import matplotlib.image as mpimg
+def augment_brightness_camera_images(image):
+    image1 = cv2.cvtColor(image,cv2.COLOR_RGB2HSV)
+    random_bright = .25+np.random.uniform()
+    #print(random_bright)
+    image1[:,:,2] = image1[:,:,2]*random_bright
+    image1 = cv2.cvtColor(image1,cv2.COLOR_HSV2RGB)
+    return image1
+def transform_image(img,ang_range,shear_range,trans_range,brightness=0):
+    '''
+    This function transforms images to generate new images.
+    The function takes in following arguments,
+    1- Image
+    2- ang_range: Range of angles for rotation
+    3- shear_range: Range of values to apply affine transform to
+    4- trans_range: Range of values to apply translations over.
+
+    A Random uniform distribution is used to generate different parameters for transformation
+
+    '''
+    # Rotation
+
+    ang_rot = np.random.uniform(ang_range)-ang_range/2
+    rows,cols,ch = img.shape    
+    Rot_M = cv2.getRotationMatrix2D((cols/2,rows/2),ang_rot,1)
+
+    # Translation
+    tr_x = trans_range*np.random.uniform()-trans_range/2
+    tr_y = trans_range*np.random.uniform()-trans_range/2
+    Trans_M = np.float32([[1,0,tr_x],[0,1,tr_y]])
+
+    # Shear
+    pts1 = np.float32([[5,5],[20,5],[5,20]])
+
+    pt1 = 5+shear_range*np.random.uniform()-shear_range/2
+    pt2 = 20+shear_range*np.random.uniform()-shear_range/2
+
+    # Brightness
+
+
+    pts2 = np.float32([[pt1,5],[pt2,pt1],[5,pt2]])
+
+    shear_M = cv2.getAffineTransform(pts1,pts2)
+
+    img = cv2.warpAffine(img,Rot_M,(cols,rows))
+    img = cv2.warpAffine(img,Trans_M,(cols,rows))
+    img = cv2.warpAffine(img,shear_M,(cols,rows))
+
+    if brightness == 1:
+      img = augment_brightness_camera_images(img)
+
+    return img
+
+image = cv2.imread('Datasets/stopsign.jpg')
+plt.imshow(image);
+plt.axis('off');
+gs1 = gridspec.GridSpec(10, 10)
+gs1.update(wspace=0.01, hspace=0.02) # set the spacing between axes.
+plt.figure(figsize=(12,12))
+for i in range(100):
+    ax1 = plt.subplot(gs1[i])
+    ax1.set_xticklabels([])
+    ax1.set_yticklabels([])
+    ax1.set_aspect('equal')
+    img = transform_image(image,20,10,5,brightness=1)
+    cv2.imwrite("Augmentation/%.3d.jpg" % i, img)
+    plt.subplot(10,10,i+1)
+    plt.imshow(img)
+    plt.axis('off')
+
+plt.show()

001.jpg

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+import cv2
+from matplotlib import pyplot as plt
+img = cv2.imread('target.png')
+
+search = cv2.dilate(img, cv2.getStructuringElement(cv2.MORPH_RECT, (5,5)))
+search = cv2.cvtColor(search, cv2.COLOR_BGR2GRAY)
+im2, contours, hierarchy = cv2.findContours(search, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+bboxes = [cv2.boundingRect(c) for c in contours]
+
+fig, axes = plt.subplots(1, sum(rect[2]*rect[3] > 250 for rect in bboxes))
+fig.set_size_inches([12,3])
+fig.tight_layout()
+figi = 0
+for i in range(len(contours)):
+    rect = cv2.boundingRect(contours[i])
+    area = rect[2] * rect[3]
+    #if area < 250:
+    if area < 4000:
+        continue
+
+    obj = img[rect[1]:rect[1]+rect[3]+1, rect[0]:rect[0]+rect[2]+1, :]
+    obj = cv2.cvtColor(obj, cv2.COLOR_BGR2RGB)
+    imgg = cv2.imread("image.jpg")
+    crop_img = imgg[rect[1]:rect[1]+rect[3]+1, rect[0]:rect[0]+rect[2]+1]
+    cv2.imwrite("%.3d.jpg" % figi, crop_img)
+    #axes[figi].imshow(obj)
+    cv2.imshow("cropped", crop_img)
+    #cv2.waitKey(0)
+    figi += 1
+
+fig.show()
+cv2.waitKey(0)

frame302.jpg

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+# import cv2;
+# katti = cv2.VideoCapture('video1.mp4');
+# success,image = katti.read()
+# count = 0
+# while success:
+# 	cv2.imwrite("evidence/video1/photo%d.jpg"%count,image)
+# 	print('photo %d', count)
+# 	count +=1
+
+
+# # import cv2
+# # import numpy as np
+# # import os
+
+# # # Playing video from file:
+# # cap = cv2.VideoCapture('video1.mp4')
+
+# # try:
+# #     if not os.path.exists('data'):
+# #         os.makedirs('data')
+# # except OSError:
+# #     print ('Error: Creating directory of data')
+
+# # currentFrame = 0
+# # while(True):
+# #     # Capture frame-by-frame
+# #     ret, frame = cap.read()
+
+# #     # Saves image of the current frame in jpg file
+# #     name = './data/frame' + str(currentFrame) + '.jpg'
+# #     print ('Creating...' + name)
+# #     cv2.imwrite(name, frame)
+
+# #     # To stop duplicate images
+# #     currentFrame += 1
+
+# # # When everything done, release the capture
+# # cap.release()
+# # cv2.destroyAllWindows()
+
+
+import cv2
+vidcap = cv2.VideoCapture('video28.mp4')
+success,image = vidcap.read()
+count = 0
+while success:
+  cv2.imwrite("Temp/frame%d.jpg" % count, image)     # save frame as JPEG file      
+  success,image = vidcap.read()
+  print('Read a new frame: ', success)
+  count += 1

image.jpg

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+# import cv2
+# import numpy as np
+
+# ## Read
+# img = cv2.imread("frame0.jpg")
+# img = cv2.resize(img, (540, 960))
+
+# ## convert to hsv
+# hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+# ## mask of green (36,0,0) ~ (70, 255,255)
+# mask1 = cv2.inRange
+# #mask1 = cv2.inRange(hsv, (170, 70, 50), (180, 255,255))
+# mask1 = cv2.inRange(hsv, (10, 100, 100), (10, 255,255))
+# ## mask o yellow (15,0,0) ~ (36, 255, 255)
+# #mask2 = cv2.inRange(hsv, (110, 50, 70), (180, 255, 255))
+# mask2 = cv2.inRange(hsv, (160, 100, 100), (180, 255, 255))
+# ## final mask and masked
+# mask = cv2.bitwise_or(mask1, mask2)
+# target = cv2.bitwise_and(img,img, mask=mask)
+# #bgr_image = cv2.cvtColor(mask1, cv2.COLOR_HSV2BGR)
+# cv2.imwrite("target.png", target)
+# cv2.imshow('target',target)
+# cv2.imshow('mask',mask)
+# cv2.imshow('mask1',mask1)
+# cv2.imshow('mask2',mask2)
+# #cv2.imshow('bgr_image',bgr_image)
+# cv2.waitKey(0)
+
+import cv2
+import numpy as np
+
+## Read
+img = cv2.imread("frame302.jpg")
+#img = cv2.resize(img, (540, 960))
+
+## convert to hsv    
+hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+## mask of green (36,0,0) ~ (70, 255,255)
+#mask1 = cv2.inRange
+#mask1 = cv2.inRange(hsv, (170, 70, 50), (180, 255,255))
+#mask1 = cv2.inRange(hsv, (-1, 70, 50), (5, 255,255))
+mask1 = cv2.inRange(hsv, (-1, 100, 100), (1, 255,255))
+## mask o yellow (15,0,0) ~ (36, 255, 255)
+#mask2 = cv2.inRange(hsv, (110, 50, 70), (180, 255, 255))
+mask2 = cv2.inRange(hsv, (130, 100, 100), (190, 255, 255))
+## final mask and masked
+mask = cv2.bitwise_or(mask1, mask2)
+target = cv2.bitwise_and(img,img, mask=mask)
+#bgr_image = cv2.cvtColor(mask1, cv2.COLOR_HSV2BGR)
+cv2.imwrite("image.jpg",img)
+cv2.imwrite("target.png", target)
+cv2.imshow('target',target)
+cv2.imshow('mask',mask)
+cv2.imshow('mask1',mask1)
+cv2.imshow('mask2',mask2)
+#cv2.imshow('bgr_image',bgr_image)
+cv2.waitKey(0)