Crop Image File

Follow along: Crop Image File

The program launching process along with parameter settings are all simplified and set up on the Jupyter Notebook Environment.
  • Create a new *.ipynb file Jupyter Notebook
  • Fill in the content below in the newly created file
  • Follow and Execute the example codes
(The Jetson Board used for these examples are => Jetson Nano)

  • 2.crop.py

import cv2
import numpy as np

# Load an image
image = cv2.imread('image.jpg')

# Define the coordinates of the ROI (top-left and bottom-right corners)
x1, y1, x2, y2 = 75, 80, 135, 140

# Crop the ROI using OpenCV
cropped_image_cv2 = image[y1:y2, x1:x2]

# Get the dimensions of the original image
height, width, _ = image.shape

# Resize the cropped image to match the dimensions of the original image
cropped_image_cv2_resized = cv2.resize(cropped_image_cv2, (width, height))

# Crop the same region using NumPy on the original image
cropped_image_numpy = image[y1:y2, x1:x2]

# Resize the cropped image using NumPy to match the dimensions of the original image
cropped_image_numpy_resized = cv2.resize(cropped_image_numpy, (width, height))

# Add text labels to the images
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(image, 'Original', (10, 30), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(cropped_image_cv2_resized, 'OpenCV', (10, 30), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
cv2.putText(cropped_image_numpy_resized, 'NumPy', (10, 30), font, 1, (255, 255, 255), 2, cv2.LINE_AA)

# Display the original and cropped images side by side
combined_image = np.hstack((image, cropped_image_cv2_resized, cropped_image_numpy_resized))
cv2.imshow('Image Cropping', combined_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

  • code progress

    1. Load input image using OpenCV.

    2. Define the coordinates of the region of interest (ROI).

    3. Crop image using slicing in OpenCV.

    4. Resize and Crop with NumPy.

    5. Display by adding a text label to each image.