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app.py

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+import streamlit as st
+import os
+import random
+from PIL import Image
+from transformers import pipeline
+import pandas as pd
+import matplotlib.pyplot as plt
+
+
+# Function to load a random image from a folder
+def load_random_image(folder_path):
+    images = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
+    random_image_path = random.choice(images)
+    return Image.open(random_image_path)
+
+# Path to your images folder
+folder_path = 'data/'
+
+# Streamlit app
+st.title('Image Classifier - Real or Fake')
+
+# Allow users to upload an image
+uploaded_image = st.file_uploader("Upload an image for classification", type=["png", "jpg", "jpeg"])
+
+# Create two columns
+col1, col2 = st.columns(2)
+
+# Display the uploaded image or a random image
+if uploaded_image is not None:
+    image = Image.open(uploaded_image)
+    col1.image(image, caption='Uploaded Image', use_column_width=True)
+else:
+    # Display a random image from the folder if no image is uploaded
+    if 'image_path' not in st.session_state or st.button('Load Random Image'):
+        st.session_state.image_path = load_random_image(folder_path)
+    col1.image(st.session_state.image_path, caption='Random Image', use_column_width=True)
+
+# Classify button
+if st.button('Classify'):
+    # This example uses a fixed classification result.
+    # You can replace this part with your actual model prediction logic.
+    pipe = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
+    
+    if uploaded_image is not None:
+        classification_results = pipe(image)
+    else:
+        classification_results = pipe(st.session_state.image_path)
+    
+    
+    # Convert the classification results to a DataFrame
+    df_results = pd.DataFrame(classification_results)
+    
+    # Plotting
+    fig, ax = plt.subplots()
+    ax.bar(df_results['label'], df_results['score'], color=['blue', 'orange'])
+    ax.set_ylabel('Scores')
+    ax.set_title('Classification Scores')
+    plt.tight_layout()
+    
+    # Display the bar chart in Streamlit
+    col2.pyplot(fig)
+    
+    # Load a new random image for next classification if no image is uploaded
+    if uploaded_image is None:
+        st.session_state.image_path = load_random_image(folder_path)

requirements.txt

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+-i https://pypi.org/simple
+altair==5.2.0 ; python_version >= '3.8'
+attrs==23.2.0 ; python_version >= '3.7'
+blinker==1.7.0 ; python_version >= '3.8'
+cachetools==5.3.3 ; python_version >= '3.7'
+certifi==2024.2.2 ; python_version >= '3.6'
+charset-normalizer==3.3.2 ; python_version >= '3.7'
+click==8.1.7 ; python_version >= '3.7'
+contourpy==1.2.0 ; python_version >= '3.9'
+cycler==0.12.1 ; python_version >= '3.8'
+filelock==3.13.1 ; python_version >= '3.8'
+fonttools==4.49.0 ; python_version >= '3.8'
+fsspec==2024.2.0 ; python_version >= '3.8'
+gitdb==4.0.11 ; python_version >= '3.7'
+gitpython==3.1.42 ; python_version >= '3.7'
+huggingface-hub==0.21.2 ; python_version >= '3.8'
+idna==3.6 ; python_version >= '3.5'
+importlib-metadata==7.0.1 ; python_version >= '3.8'
+jinja2==3.1.3 ; python_version >= '3.7'
+jsonschema==4.21.1 ; python_version >= '3.8'
+jsonschema-specifications==2023.12.1 ; python_version >= '3.8'
+kiwisolver==1.4.5 ; python_version >= '3.7'
+markdown-it-py==3.0.0 ; python_version >= '3.8'
+markupsafe==2.1.5 ; python_version >= '3.7'
+matplotlib==3.8.3
+mdurl==0.1.2 ; python_version >= '3.7'
+mpmath==1.3.0
+networkx==3.2.1 ; python_version >= '3.9'
+numpy==1.26.4 ; python_version >= '3.9'
+packaging==23.2 ; python_version >= '3.7'
+pandas==2.2.1 ; python_version >= '3.9'
+pillow==10.2.0
+protobuf==4.25.3 ; python_version >= '3.8'
+pyarrow==15.0.0 ; python_version >= '3.8'
+pydeck==0.8.1b0 ; python_version >= '3.7'
+pygments==2.17.2 ; python_version >= '3.7'
+pyparsing==3.1.1 ; python_full_version >= '3.6.8'
+python-dateutil==2.8.2 ; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
+pytz==2024.1
+pyyaml==6.0.1 ; python_version >= '3.6'
+referencing==0.33.0 ; python_version >= '3.8'
+regex==2023.12.25 ; python_version >= '3.7'
+requests==2.31.0 ; python_version >= '3.7'
+rich==13.7.1 ; python_version >= '3.7'
+rpds-py==0.18.0 ; python_version >= '3.8'
+safetensors==0.4.2 ; python_version >= '3.7'
+six==1.16.0 ; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
+smmap==5.0.1 ; python_version >= '3.7'
+streamlit==1.31.1
+sympy==1.12 ; python_version >= '3.8'
+tenacity==8.2.3 ; python_version >= '3.7'
+tokenizers==0.15.2 ; python_version >= '3.7'
+toml==0.10.2 ; python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'
+toolz==0.12.1 ; python_version >= '3.7'
+torch==2.2.1
+tornado==6.4 ; python_version >= '3.8'
+tqdm==4.66.2 ; python_version >= '3.7'
+transformers==4.38.1
+typing-extensions==4.10.0 ; python_version >= '3.8'
+tzdata==2024.1 ; python_version >= '2'
+tzlocal==5.2 ; python_version >= '3.8'
+urllib3==2.2.1 ; python_version >= '3.8'
+validators==0.22.0 ; python_version >= '3.8'
+zipp==3.17.0 ; python_version >= '3.8'