Data Science With Python | Python Data Science Tutorial | Data Science App with Python and Streamlit
Certainly! To build your first data science app using Streamlit, you can follow these steps. We'll create a simple app that allows users to upload an image, perform basic image processing, and display the results. Make sure you have Python installed on your machine.
Step 1: Install Streamlit
Open your terminal or command prompt and run:
bash
pip install streamlit
Step 2: Create a new Python script
Create a new Python script (e.g., image_app.py) using a text editor of your choice.
Step 3: Write the Streamlit app code
Copy and paste the following code into your image_app.py file:
python
image_app.py
import streamlit as st
from PIL import Image
import numpy as np
def main():
st.title("Image Processing App")
Upload image through Streamlit
uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
if uploaded_image is not None:
Display the uploaded image
image = Image.open(uploaded_image)
st.image(image, caption="Uploaded Image", use_column_width=True)
Perform image processing (you can customize this part)
grayscale_image = image.convert("L")
st.image(grayscale_image, caption="Grayscale Image", use_column_width=True)
Basic image statistics
image_array = np.array(image)
st.text(f"Image Shape: {image_array.shape}")
st.text(f"Image Mean: {np.mean(image_array)}")
st.text(f"Image Standard Deviation: {np.std(image_array)}")
if _name_ == "__main__":
main()
Step 4: Run the Streamlit app
Open your terminal or command prompt, navigate to the directory containing image_app.py, and run:
bash
streamlit run image_app.py
Streamlit will start a local development server, and you can view your app in a web browser by going to the provided URL (usually http://localhost:8501).
Step 5: Use your app
Visit the Streamlit app URL in your web browser, upload an image, and see the basic image processing results.
Feel free to modify the code to add more sophisticated image processing or integrate machine learning models based on your learning goals and interests. Streamlit is a powerful tool for creating interactive and user-friendly data science applications.
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