Create app.py

app.py

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+import streamlit as st
+import numpy as np
+import pandas as pd
+from sklearn.datasets import fetch_openml
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+import scipy.ndimage.interpolation as ndi_int
+
+# Streamlit App title
+st.title("Image Shifting with MNIST Dataset")
+
+# Load the MNIST dataset
+st.write("Loading the MNIST dataset...")
+mnist = fetch_openml('mnist_784', version=1)
+
+# Separate the data and target variables
+X, y = mnist["data"], mnist["target"].astype(int)
+
+# Select a sample digit to display
+st.sidebar.write("## Shift the Image")
+digit_index = st.sidebar.slider("Select a digit index", 0, X.shape[0] - 1, 0)
+digit = X.iloc[digit_index, :].values
+digit_img = digit.reshape(28, 28)
+
+# Display original digit image
+st.write("### Original Image")
+fig, ax = plt.subplots()
+ax.imshow(digit_img, cmap=mpl.cm.binary)
+ax.axis("off")
+st.pyplot(fig)
+
+# Function to shift the image
+def shift_image(digit_img, x_shift, y_shift):
+    return ndi_int.shift(digit_img, [x_shift, y_shift])
+
+# Input for shifting the image
+x_shift = st.sidebar.slider("Shift in X (horizontal)", -10, 10, 0)
+y_shift = st.sidebar.slider("Shift in Y (vertical)", -10, 10, 0)
+
+# Shift the image based on user input
+shifted_image = shift_image(digit_img, x_shift, y_shift)
+
+# Display shifted image
+st.write("### Shifted Image")
+fig_shifted, ax_shifted = plt.subplots()
+ax_shifted.imshow(shifted_image, cmap=mpl.cm.binary)
+ax_shifted.axis("off")
+st.pyplot(fig_shifted)