Create app.py

app.py

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+# Install necessary libraries
+!pip install streamlit plotly transformers
+
+# Import libraries
+import streamlit as st
+from PIL import Image
+import numpy as np
+import plotly.graph_objects as go
+from transformers import pipeline  # Hugging Face's pipeline API, optional
+
+# Streamlit App Configuration
+st.title("3D Image Converter")
+st.sidebar.header("Upload Image")
+
+# Upload Image
+uploaded_file = st.sidebar.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
+
+if uploaded_file is not None:
+    # Load Image
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    # Convert Image to Grayscale for Simplicity
+    grayscale_image = image.convert("L")
+    
+    # Create 3D Surface Plot
+    z_data = np.asarray(grayscale_image)
+    x_data, y_data = np.meshgrid(range(z_data.shape[1]), range(z_data.shape[0]))
+
+    # Create a 3D Surface Plot using Plotly
+    fig = go.Figure(data=[go.Surface(z=z_data, x=x_data, y=y_data, colorscale='gray')])
+    fig.update_layout(scene=dict(zaxis=dict(title='Height'),
+                                 xaxis=dict(title='Width'),
+                                 yaxis=dict(title='Depth')),
+                      title="3D Representation of Image")
+    
+    st.plotly_chart(fig)
+
+    # Option to Save 3D Data
+    save_button = st.sidebar.button("Save 3D Data")
+    if save_button:
+        np.save("3d_image_data.npy", z_data)
+        st.sidebar.success("3D data saved as 3d_image_data.npy!")
+
+# Optional: Integrate Hugging Face models for advanced transformations
+if st.sidebar.checkbox("Apply Hugging Face Transformation"):
+    st.sidebar.text("Using Transformers API...")
+    model = pipeline("image-to-image", model="stabilityai/stable-diffusion")  # Replace with appropriate Hugging Face model
+    result = model(uploaded_file)
+    st.image(result["output_image"], caption="Transformed Image", use_column_width=True)
+
+# Note for Colab users:
+# Streamlit applications are designed to run locally. Use the command below in a Colab cell to launch the app:
+# !streamlit run your_script_name.py
+# After running the command, Colab will provide a public URL to access the Streamlit app.