Getting the image

We will read the image using an OpenCV method. We will resize it for making it easier to be viewed.
Then, we will make it into a blob which is a 4-dimensional array of images using cv2.dnn.blobFromImage.
We also do the following steps
- Normalising pixel values by dividing by 255
- Fixing the size to 608x608 required by Yolo
- Swapping OpenCV's default BGR format to RGB

INSTRUCTIONS

Read the image using cv2.imread():

img=<< your code comes here >>("/cxldata/projects/yolov4/soccer.jpg")

Resize the image using cv2.resize().

img=<< your code comes here >>(img, (608, 608))

Print the image size and get H,W the height and width of the image:
```
print (img.shape)
(H, W) = img.shape[:2]
```
Show the image:
```
plt.imshow(fixColor(img))
```
Use the cv2.dnn.blobFromImage to read the image as a blob, normalize it, fix the size of the image, and set the image channels as or OpenCV.
```
blob = cv2.dnn.blobFromImage(img, 1 / 255.0, (608, 608), swapRB=True, crop=False)
```
Print the blob shape:
```
print ("Shape of blob", blob.shape)
```

We can see the individual color streams of the image:

split_blob=np.hstack([ blob[0, 0, :, :],blob[0, 1, :, :], blob[0, 2, :, :],])
plt.imshow(fixColor(split_blob))

See Answer

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