File size: 2,180 Bytes
e38bf4d d243d0e 8820453 d243d0e aec5ec6 8820453 014d1cd d243d0e b13bb13 d243d0e 9b319b3 b13bb13 9b319b3 aec5ec6 b13bb13 8820453 aec5ec6 b13bb13 d243d0e b13bb13 d243d0e a655cfe d243d0e aec5ec6 d243d0e 8820453 b13bb13 8820453 f51b0f2 8820453 a655cfe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 |
import numpy as np
import gradio as gr
from skimage import color
from sklearn.decomposition import TruncatedSVD
from PIL import Image
def truncated_svd_compress(image, k):
"""Compress the image using Truncated SVD by keeping only the top k singular values."""
svd = TruncatedSVD(n_components=k)
U = svd.fit_transform(image)
S = svd.singular_values_
Vt = svd.components_
compressed_image = np.dot(U, np.dot(np.diag(S), Vt))
return compressed_image
def process_image(image, k):
"""Process the uploaded image, compress it using Truncated SVD, and return the result."""
# Convert PIL Image to NumPy array
image_np = np.array(image)
# Convert to grayscale for SVD
gray_image = color.rgb2gray(image_np)
# Ensure the image is 2D for SVD
if len(gray_image.shape) == 3:
gray_image = gray_image[:, :, 0]
# Compress the image using Truncated SVD
compressed_image = truncated_svd_compress(gray_image, k)
# Normalize the compressed image to the range [0, 255] and convert to uint8
compressed_image = np.clip(compressed_image, 0, 1) # Ensure values are within [0, 1]
compressed_image = (compressed_image * 255).astype(np.uint8)
# Convert compressed image back to PIL Image for Gradio output
compressed_image_pil = Image.fromarray(compressed_image)
# Ensure the PIL Image is in RGB mode for consistent display
if compressed_image_pil.mode != 'RGB':
compressed_image_pil = compressed_image_pil.convert('RGB')
return compressed_image_pil
# Gradio interface
gr_interface = gr.Interface(
fn=process_image, # Image processing function
inputs=[
gr.Image(type="pil", label="Upload Image"),
gr.Slider(1, 100, step=1, value=50, label="Compression Rank") # Compression rank slider
],
outputs=gr.Image(type="pil", label="Compressed Image"),
title="Interactive Image Compression using Truncated SVD",
description="Upload an image and adjust the compression rank to see the compressed version. The app compresses the image while retaining important features."
)
# Launch the Gradio interface
gr_interface.launch()
|