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15class_99.8.h5

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17class_98.1.h5

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44class_96.5.h5

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README (1).md

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+---
+title: EyeDiseaseClassifier
+emoji: 👁
+colorFrom: purple
+colorTo: gray
+sdk: gradio
+sdk_version: 3.16.2
+app_file: app.py
+pinned: true
+license: apache-2.0
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

README (2).md

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+---
+title: Skin Disease Classifier
+emoji: 👁
+colorFrom: gray
+colorTo: purple
+sdk: streamlit
+sdk_version: 1.41.1
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

README.md

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 ---
-title: MEDIGPT
-emoji: 🌖
-colorFrom: pink
-colorTo: red
-sdk: gradio
-sdk_version: 5.9.1
+title: Brain Tumor And Alzheimer Detection
+emoji: 😻
+colorFrom: yellow
+colorTo: pink
+sdk: streamlit
+sdk_version: 1.34.0
 app_file: app.py
 pinned: false
 ---

alzheimer_99.5.h5

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app.py

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+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1sjyLFLqBccpUzaUi4eyyP3NYE3gDtHfs
+"""
+
+!pip install gradio
+import gradio as gr
+from fastai.vision.all import load_learner
+from PIL import Image
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from torchvision import transforms
+
+# Model paths for all disease types
+model_path_skin_disease = 'multi_weight.pth'  # Skin Disease Model
+model_path_brain_tumor = 'brain_tumor_model.pkl'
+model_path_alzheimers = 'alzheimers_model.pkl'
+model_path_eye_disease = 'eye_disease_model.pkl'
+
+# Load models
+skin_disease_model = torch.load(model_path_skin_disease)  # For Skin Disease model
+brain_tumor_model = load_learner(model_path_brain_tumor)
+alzheimers_model = load_learner(model_path_alzheimers)
+eye_disease_model = load_learner(model_path_eye_disease)
+
+# Diagnosis Map for Skin Disease Model
+DIAGNOSIS_MAP = {
+    0: 'Melanoma',
+    1: 'Melanocytic nevus',
+    2: 'Basal cell carcinoma',
+    3: 'Actinic keratosis',
+    4: 'Benign keratosis',
+    5: 'Dermatofibroma',
+    6: 'Vascular lesion',
+    7: 'Squamous cell carcinoma',
+    8: 'Unknown'
+}
+
+# Image Preprocessing for Skin Disease Model
+transform = transforms.Compose([
+    transforms.Resize(256),
+    transforms.CenterCrop(224),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+# Skin Disease Prediction Function
+def predict_skin_disease(img: Image.Image):
+    img_tensor = transform(img).unsqueeze(0)
+    with torch.no_grad():
+        outputs = skin_disease_model(img_tensor)
+        probs = F.softmax(outputs, dim=1)
+        top_probs, top_idxs = torch.topk(probs, 3, dim=1)  # top 3 predictions
+
+    predictions = []
+    for prob, idx in zip(top_probs[0], top_idxs[0]):
+        label = DIAGNOSIS_MAP.get(idx.item(), "Unknown")
+        confidence = prob.item() * 100
+        predictions.append(f"{label}: {confidence:.2f}%")
+
+    return "\n".join(predictions)
+
+# Brain Tumor Prediction Function
+def predict_brain_tumor(image):
+    pred, _, prob = brain_tumor_model.predict(image)
+    return f"Prediction: {pred}, Probability: {prob.max():.2f}"
+
+# Alzheimer's Prediction Function
+def predict_alzheimers(image):
+    pred, _, prob = alzheimers_model.predict(image)
+    return f"Prediction: {pred}, Probability: {prob.max():.2f}"
+
+# Eye Disease Prediction Function
+def predict_eye_disease(image):
+    pred, _, prob = eye_disease_model.predict(image)
+    return f"Prediction: {pred}, Probability: {prob.max():.2f}"
+
+# Gradio Interface Function
+def main():
+    # Image input component
+    image_input = gr.inputs.Image(shape=(224, 224), image_mode='RGB')
+
+    # Dropdown to choose disease type
+    model_choice = gr.inputs.Dropdown(choices=[
+        "Skin Disease", "Brain Tumor", "Alzheimer's Detection", "Eye Disease"],
+        label="Select Disease Type")
+
+    # Gradio tabs for each category
+    with gr.Blocks() as demo:
+        gr.Markdown("# Medical Image Classifier Dashboard")
+
+        with gr.Tab("Skin Disease Prediction"):
+            with gr.Column():
+                gr.Markdown("Upload a skin lesion image for diagnosis prediction.")
+                image_input_skin = gr.Image(type="pil", label="Upload Skin Lesion Image")
+                output_skin = gr.Textbox(label="Prediction Results")
+                image_input_skin.change(predict_skin_disease, inputs=image_input_skin, outputs=output_skin)
+
+        with gr.Tab("Brain Tumor Prediction"):
+            with gr.Column():
+                gr.Markdown("Upload a brain scan image for tumor classification.")
+                image_input_brain = gr.Image(type="pil", label="Upload Brain Scan Image")
+                output_brain = gr.Textbox(label="Prediction Results")
+                image_input_brain.change(predict_brain_tumor, inputs=image_input_brain, outputs=output_brain)
+
+        with gr.Tab("Alzheimer's Prediction"):
+            with gr.Column():
+                gr.Markdown("Upload a brain image for Alzheimer's detection.")
+                image_input_alz = gr.Image(type="pil", label="Upload Alzheimer's Image")
+                output_alz = gr.Textbox(label="Prediction Results")
+                image_input_alz.change(predict_alzheimers, inputs=image_input_alz, outputs=output_alz)
+
+        with gr.Tab("Eye Disease Prediction"):
+            with gr.Column():
+                gr.Markdown("Upload an image for eye disease classification.")
+                image_input_eye = gr.Image(type="pil", label="Upload Eye Disease Image")
+                output_eye = gr.Textbox(label="Prediction Results")
+                image_input_eye.change(predict_eye_disease, inputs=image_input_eye, outputs=output_eye)
+
+    demo.launch()
+
+# Run the Gradio app
+if __name__ == "__main__":
+    main()

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model3-86%.pkl

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requirements (1).txt

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+fastai==2.7.10
+fastbook==0.0.29
+Flask==2.2.2
+Flask-Cors==3.0.10
+gradio==3.0
+torch==1.13.1
+torchvision==0.14.1

requirements (2).txt

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+streamlit==1.25.0
+torch==2.0.1
+torchvision==0.15.2
+efficientnet-pytorch==0.7.1
+Pillow==9.5.0

requirements.txt

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+protobuf==3.20.3
+tensorflow==2.12.0
+streamlit==1.22.0
+streamlit-option-menu==0.3.12