Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,93 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import os
+import mimetypes
+import cv2
+import uuid
 import streamlit as st
+from google import generativeai as genai
+import pywhatkit as pw
 
-"""
-# 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).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-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])),
-    ))
+# Configure Gemini API
+def configure_api():
+    api_key = "AIzaSyBDkLcFKzE_T6r1E5XjbuXVaoW40Szn71s"  # Use your real key here
+    genai.configure(api_key=api_key)
+    return genai.GenerativeModel('gemini-2.0-flash')
+
+def capture_from_webcam():
+    cam = cv2.VideoCapture(0)
+    if not cam.isOpened():
+        st.error("Could not open webcam.")
+        return None
+
+    st.info("Capturing image... Press SPACE to capture.")
+    filename = "ahmad.jpg"
+    while True:
+        ret, frame = cam.read()
+        if not ret:
+            st.error("Failed to grab frame.")
+            break
+
+        cv2.imshow("Camera Feed - Press SPACE to capture", frame)
+        key = cv2.waitKey(1)
+        if key % 256 == 32:  # SPACE pressed
+            cv2.imwrite(filename, frame)
+            break
+        elif key % 256 == 27:  # ESC
+            break
+
+    cam.release()
+    cv2.destroyAllWindows()
+    if os.path.exists(filename):
+        return filename
+    return None
+
+def process_image(image_path, model):
+    mime_type, _ = mimetypes.guess_type(image_path)
+    if not mime_type:
+        mime_type = "image/jpeg"
+
+    with open(image_path, "rb") as img_file:
+        image_data = img_file.read()
+
+    response = model.generate_content(
+        [
+            {"mime_type": mime_type, "data": image_data},
+            """complete analyze the given picture pay attention any detail of picture and tell which pakistani song is suitble according person in picture 
+            just give me the name of one hindi song according to peroson in pic and just give the name of song no other detail just name ."""
+        ]
+    )
+    return response.text.strip()
+
+# Streamlit UI
+st.set_page_config(page_title="Hindi Song Recommender", layout="centered")
+st.title("🎶 Hindi Song Recommender from Image")
+
+st.write("### Aap image kaise doge?")
+option = st.radio("Choose input method:", ["Upload Image", "Capture from Webcam"])
+
+model = configure_api()
+
+if option == "Upload Image":
+    uploaded_file = st.file_uploader("Drag and drop your image here", type=["jpg", "jpeg", "png"])
+    if uploaded_file:
+        path = f"temp_{uuid.uuid4().hex[:8]}.jpg"
+        with open(path, "wb") as f:
+            f.write(uploaded_file.read())
+        st.session_state.image_path = path
+        st.image(path, caption="Uploaded Image", use_container_width=True)
+
+elif option == "Capture from Webcam":
+    if st.button("Capture Image from Webcam"):
+        path = capture_from_webcam()
+        if path:
+            st.session_state.image_path = path
+            st.image(path, caption="Captured Image", use_container_width=True)
+
+if "image_path" in st.session_state and st.button("Suggest Hindi Song"):
+    with st.spinner("Analyzing image and finding a song..."):
+        try:
+            suggested_song = process_image(st.session_state.image_path, model)
+            st.success(f"🎵 Suggested Hindi Song: {suggested_song}")
+            pw.playonyt(suggested_song)
+            st.info("Playing song on YouTube...")
+        except Exception as e:
+            st.error(f"Error: {e}")