push

app.py

@@ -0,0 +1,64 @@
+import os
+import streamlit as st
+import tensorflow as tf
+import numpy as np
+
+# Loading the saved model
+model = tf.keras.models.load_model('model.h5')
+
+def predict(input_image):
+    try:
+        # Preprocessing
+        input_image = tf.convert_to_tensor(input_image)
+        input_image = tf.image.resize(input_image, [224, 224])
+        input_image = tf.expand_dims(input_image, 0) / 255.0
+
+        # Prediction
+        predictions = model.predict(input_image)
+        labels = ['Cataract', 'Conjunctivitis', 'Glaucoma', 'Normal']
+
+        # Get confidence score for each class
+        disease_confidence = {label: np.round(predictions[0][idx] * 100, 3) for idx, label in enumerate(labels)}
+
+        # Get confidence percentage for the "Normal" class
+        normal_confidence = disease_confidence['Normal']
+
+        # Check if Normal confidence is greater than 50%
+        if normal_confidence > 50:
+            return f"""Congrats! no disease detected 
+            Normal with confidence: {normal_confidence}%"""
+
+
+        output_lines = [f"\n{disease}: {confidence}%" for disease, confidence in disease_confidence.items()]
+        output_string = "\n".join(output_lines[:-1])
+        return output_string
+
+
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+# Example images directory
+examples = [os.path.join("example", file) for file in os.listdir("example")]
+
+# Streamlit app
+st.title("👁️ Eye Disease Detection")
+st.write("This model identifies common eye diseases such as Cataract, Conjunctivitis, and Glaucoma. Upload an eye image to see how the model classifies its condition.")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png"])
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    image = tf.image.decode_image(uploaded_file.read(), channels=3)
+    image_np = image.numpy()
+    st.image(image_np, caption='Uploaded Image.', use_column_width=True)
+
+    # Perform prediction
+    prediction = predict(image_np)
+    st.write("Prediction:")
+    st.write(prediction)
+
+# Display examples images
+st.write("Examples:")
+cols = st.columns(len(examples))
+for idx, example in enumerate(examples):
+    cols[idx].image(example, caption=os.path.basename(example))

model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0503e25aadd98e95209163181ac975dd0c2a27740e5e2d5751e8fc661ee4b454
+size 157265144

requirement.txt

@@ -0,0 +1,134 @@
+absl-py==2.0.0
+aiofiles==23.2.1
+altair==5.3.0
+annotated-types==0.6.0
+anyio==4.3.0
+appdirs==1.4.4
+astunparse==1.6.3
+attrs==23.2.0
+autograd==1.6.2
+autoray==0.6.9
+blinker==1.7.0
+cachetools==5.3.2
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.0
+cycler==0.12.1
+dill==0.3.8
+fastapi==0.110.2
+ffmpy==0.3.2
+filelock==3.13.1
+Flask==3.0.2
+flatbuffers==23.5.26
+fonttools==4.47.0
+fsspec==2024.2.0
+future==1.0.0
+gast==0.4.0
+gitdb==4.0.11
+GitPython==3.1.43
+google-auth==2.25.2
+google-auth-oauthlib==1.0.0
+google-pasta==0.2.0
+gradio==4.27.0
+gradio_client==0.15.1
+grpcio==1.60.0
+h11==0.14.0
+h5py==3.10.0
+httpcore==1.0.5
+httpx==0.27.0
+huggingface-hub==0.22.2
+idna==3.6
+importlib_resources==6.4.0
+itsdangerous==2.1.2
+jax==0.4.23
+Jinja2==3.1.3
+joblib==1.3.2
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+keras==2.15.0
+kiwisolver==1.4.5
+libclang==16.0.6
+Markdown==3.5.1
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+matplotlib==3.8.2
+mdurl==0.1.2
+ml-dtypes==0.2.0
+mpmath==1.3.0
+networkx==3.2.1
+numpy==1.23.5
+oauthlib==3.2.2
+opencv-python==4.8.1.78
+opt-einsum==3.3.0
+orjson==3.10.1
+packaging==23.2
+pandas==2.1.4
+pbr==6.0.0
+PennyLane==0.35.1
+PennyLane_Lightning==0.35.1
+Pillow==10.1.0
+ply==3.11
+protobuf==4.23.4
+psutil==5.9.8
+pyarrow==16.0.0
+pyasn1==0.5.1
+pyasn1-modules==0.3.0
+pydantic==2.7.0
+pydantic_core==2.18.1
+pydeck==0.8.1b0
+pydub==0.25.1
+Pygments==2.17.2
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-multipart==0.0.9
+pytz==2023.3.post1
+PyYAML==6.0.1
+qiskit==1.0.1
+qiskit-aer==0.13.3
+qiskit-terra==0.46.0
+referencing==0.34.0
+requests==2.31.0
+requests-oauthlib==1.3.1
+rich==13.7.1
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.4.1
+rustworkx==0.14.1
+scikit-learn==1.3.2
+scipy==1.11.4
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+smmap==5.0.1
+sniffio==1.3.1
+starlette==0.37.2
+stevedore==5.2.0
+streamlit==1.33.0
+symengine==0.11.0
+sympy==1.12
+tenacity==8.2.3
+tensorboard==2.15.1
+tensorboard-data-server==0.7.2
+tensorflow==2.15.0
+tensorflow-estimator==2.15.0
+tensorflow-intel==2.15.0
+tensorflow-io-gcs-filesystem==0.31.0
+termcolor==2.4.0
+threadpoolctl==3.2.0
+toml==0.10.2
+tomlkit==0.12.0
+toolz==0.12.1
+torch==2.2.0
+tornado==6.4
+tqdm==4.66.2
+typer==0.12.3
+typing_extensions==4.9.0
+tzdata==2023.3
+urllib3==2.1.0
+uvicorn==0.29.0
+watchdog==4.0.0
+websockets==11.0.3
+Werkzeug==3.0.1
+wrapt==1.14.1