Delete app1.py

app1.py

@@ -1,65 +0,0 @@
-import streamlit as st
-import tensorflow as tf
-from PIL import Image
-import numpy as np
-import sys
-
-# Create a Streamlit app
-st.title("Brain Tumor Detection")
-
-# Upload an image or multiple images
-images = st.file_uploader("Upload MRI images of brains", type=["jpg", "jpeg", "png"], accept_multiple_files=True)
-
-# Check if TensorFlow is available
-if 'tensorflow' not in sys.modules:
-    st.warning("TensorFlow is not available in this environment. Please ensure that you have the correct environment activated.")
-else:
-    # Load the TensorFlow model from the .h5 file
-    model = tf.keras.models.load_model("model.h5")
-
-    # Threshold for tumor detection
-    threshold = 0.1
-
-    if images:
-        st.write("Analyzed uploaded images...")
-        for image in images:
-            # Display the original image
-            st.image(image, caption="Uploaded Image", use_column_width=True)
-
-            # Preprocess the image
-            image = Image.open(image)
-            image = image.resize((128, 128))  # Resize to match model's input size
-            image = np.array(image)
-            image = image / 255.0  # Normalize
-            image = np.expand_dims(image, axis=0)  # Add batch dimension
-
-            # Make predictions
-            predictions = model.predict(image)
-
-            # Extract the prediction probability for the positive class
-            tumor_probability = predictions[0][1]
-
-            # Calculate the average probability of tumor detection
-            average_probability = np.mean(tumor_probability)
-
-            # Check if the average probability is greater than the threshold
-            if average_probability > threshold:
-                st.write("Prediction: Tumor detected with confidence {:.2f}".format(average_probability))
-            else:
-                st.write("Prediction: No tumor detected with confidence {:.2f}".format(2 - average_probability))
-
-
-            # Add a separator between images
-            st.write("---")
-
-# User instructions
-st.sidebar.header("Instructions")
-st.sidebar.markdown(
-    """
-    - Upload MRI images of brains using the file uploader.
-    - The app will analyze and provide predictions for each image.
-    - A confidence score is displayed to indicate prediction confidence.
-    - Adjust the threshold for tumor detection as needed.
-    - Explore different images to evaluate the model's performance.
-    """
-)