Use a Bootstrap class to add rounded corners on the image.
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Use a Bootstrap class to add rounded corners on the image.
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- The parameter has to be adjusted. The size of the image cannot be supported. A minimum of 40 pixels and a maximum of 2600 pixels must be used for each picture dimension.Write htmi code for the given image. Create a div having background-color = red. =EXPERIMENT: Observing the Image Loader while enabling a debugging capability using global flags Write down all of the steps of the experiment.
- Create empty images for Ix, Iy, Ixx, Iyy, and Ixy (all the same dimensions as your original image) Loop through pixels of image and fill in values for Ix, Iy, Ixx, Iyy, and Ixy (ignore the edges when you set up the range of your loops) Create empty image to hold "cornerness" values Loop through pixels of image Access the a neighborhood surrounding each pixel (start with a 3x3, you can expand it later if you'd like) Sum up all the Ixx, Iyy, and Ixy values in this neighborhood Compute the determinant of the M matrix Compute the trace of the M matrix Compute the "cornerness" value for the center pixel - store in the "cornerness" image Find max cornerness value in imageset threshold = 0.01(max C value) loop through pixels. if(C at pixel) > threshold: cv2.circle(image(X,Y),size(b,g,r) - 1) Do not make use of any existing functions/code that extract features. Use opencv and python.Create empty images for Ix, Iy, Ixx, Iyy, and Ixy (all the same dimensions as your original image) Loop through pixels of image and fill in values for Ix, Iy, Ixx, Iyy, and Ixy (ignore the edges when you set up the range of your loops) Create empty image to hold "cornerness" values Loop through pixels of image Access the a neighborhood surrounding each pixel (start with a 3x3, you can expand it later if you'd like) Sum up all the Ixx, Iyy, and Ixy values in this neighborhood Compute the determinant of the M matrix Compute the trace of the M matrix Compute the "cornerness" value for the center pixel - store in the "cornerness" image find max cornerness value in imageset threshold = 0.01(max C value) loop through pixels. if(C at pixel) > threshold: cv2.circle(image(X,Y),size(b,g,r) - 1) Do may not make use of any existing functions/code that extract features. Use opencv and python. Also don't use sobel.EXPERIMENT: Watching the Image Loader using e global flags to enable a debugging feature Write all steps of experiement.
- x = zeros(uint8(5,5)); for i = 1:5 for j = 1:5 a = 5/i; x(i,j) = 255/a; end end Which of the following best describes the black and white image x? 1. The columns of x will get lighter from left to right 2. The rows of x will get lighter from top to bottom 3. The rows of x will get darker from top to bottom 4. The columns of x will get darker from left to rightAdjust the parameter. Image size is unsupported. Each image dimension must utilize 40–2600 pixels.MipMaps I Suppose that a pixel projects to an area of 10x28 texels in a texture map. From what mipmap level does the texture unit look up the texture value for this pixel, if the texture unit is using "nearest" lookup for mipmaps? Enter a single integer that is the mipmap level. A/
- Fulfill the test case in the provided notepad++ image Note: do not replace anything in the notepadd++ image Here is "w04c_ans.py" follow the function constrainst in the provided image and make sure to run "w04c_test_public" with the same folder with "w04c_ans.py" and check if the test case is fulfilled def print_frame(): pass def is_valid_num(): return False def main(): while True: num_frames = input('Enter number of frames from 2 to 10 inclusive: ') if not is_valid_num(num_frames): print('Entered input is either not a number or is not between 2 and 10 inclusive. Please try again.') continue num_frames = int(num_frames) print_frame(num_frames) break if __name__ == '__main__': main() This is not a graded assignment. I just need some helpwhat I have so far but it is not working I tried to add an image file to my page body {font-family: Georgia, serif;font-size: 100%;line-height: 175%;margin: 0 15% 0;background-color:rgb(210,220,157);background-image: url(bullseye.png); /* Rounded Shape image */background-size: contain;}header {margin-top: 0;padding: 3em 1em 2em 1em;text-align: center;border-radius:4px;background-color:hsl(0, 14%, 95%);opacity:0.5;background-image: url(purpledot.png); /*purple image*/background-repeat: repeat-x;}a {text-decoration: none;color:rgb(153,51,153);}a:visited{color: hsl(300, 13%, 51%);}a:hover{background-color: #fff;}a:focus{background-color: #fff;}a:active{color:#ff00ff;}h1 {font: bold 1.5em Georgia, serif;text-shadow: 0.1em 0.1em 0.2em gray;color: rgb(153,51,153);}h2 {font-size: 1em;text-transform: uppercase;letter-spacing: 0.5em;text-align: center;color:rgb(204,102,0);}dt {font-weight: bold;}strong {font-style: italic;}ul {list-style-type: none;margin: 0;padding: 0;}#info p {font-style:…b) Modify to the following code to shift, rotate and crop the image. You can choose the coordinates of shifting yourself. ##prettyface.py #import matplotlib.pyplot as plt from scipy import ndimage from scipy import miscface = misc.face(gray=True) plt.imshow (face) plt.imshow (face, cmap-plt.cm.gray) plt.show() Submit separately as a python file.