Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,31 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# Dummy model function (replace this with your own)
+def model(input_image):
+    # Example: convert to grayscale and return message
+    gray = cv2.cvtColor(np.array(input_image), cv2.COLOR_RGB2GRAY)
+    output_image = Image.fromarray(gray)
+    result_text = "Image processed successfully"
+    return input_image, 'you are sleepy'
 
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
+st.title("📷 Webcam Image Processor")
 
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
+# Webcam input using Streamlit's native method
+img_file_buffer = st.camera_input("Take a picture")
 
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
+if img_file_buffer is not None:
+    # Convert captured image to PIL Image
+    input_image = Image.open(img_file_buffer)
 
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
+    st.subheader("🔍 Input Image")
+    st.image(input_image, caption="Captured Image", use_column_width=True)
 
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
+    # Run through model
+    output_image, result_text = model(input_image)
 
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+    st.subheader("🧠 Model Output")
+    st.image(output_image, caption="Processed Output", use_column_width=True)
+    st.success(result_text)