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Notes

Machine Learning Code Snippets

  1. Uploading the data in the code run-time :

shell from google.colab import files uploaded = files.upload()

  1. Mounting the Google Drive 
from google.colab import drive
drive.mount('/content/gdrive')

#then upload the data in the google drive and then acces sit
test_data = pd.read_csv('/content/gdrive/My Drive/Housing-Price-Prediction/data/test.csv')
  1. Directly uploading to the Current VM Instance :

shell !wget https://github.com/harshityadav95/Notex/blob/master/src/hyembosslogo.jpg

  1. Display Image in Jupyter Notebook

shell ## To display image on the Jupyter notebook from IPython.display import display display(image)

  1. Inspecting the Image type and Details :

shell import inspect print("The type of the image is " + str(type(image))) inspect.getmro(type(image))

  1. Open and Save Image

```shell import PIL from PIL import Image from IPython.display import display file="readonly/msi_recruitment.gif" image=Image.open(file) image.save("msi_recruitment.png") image=Image.open("msi_recruitment.png")

```

  1. Image Filter Library Pillow

shell from PIL import ImageFilter help(ImageFilter)

  1. Dimensions of the Image

shell display(image.crop((50,0,190,150)))

  1. Blur an Image using in built feature

shell image=image.convert('RGB') # this stands for red, green blue mode other is CMYK blurred_image=image.filter(PIL.ImageFilter.BLUR) display(blurred_image)

  1. Cropping the Image

    shell display(image.crop((50,0,190,150)))

  2. Write Text on Image

    python from PIL import ImageDraw drawing_object=ImageDraw.Draw(image) drawing_object.rectangle((50,0,190,150), fill = None, outline ='red') display(image)

12 . Enhance Image

from PIL import ImageEnhance
# load image in enhancer class
enhancer=ImageEnhance.Brightness(image)
images=[]
for i in range(0, 10):

    images.append(enhancer.enhance(i/10))

print(images)
  1. Create a new Image 
# new image with RGB mode and dimensionnina  tuple
contact_sheet=PIL.Image.new(first_image.mode, (first_image.width*3,first_image.height*3))

  1. Iterate over a 3X3 Image and Paste Image

    ```python x=0 y=0

    for img in images[1:]:

    contact_sheet.paste(img, (x, y) )

if x+first_image.width == contact_sheet.width:
    x=0
    y=y+first_image.height
else:
    x=x+first_image.width

    ```

  2. Resize an Image

    ```python contact_sheet = contact_sheet.resize((int(contact_sheet.width/2),int(contact_sheet.height/2) ))

    Now lets display that composite image

    display(contact_sheet) ```