Update app.py

app.py

@@ -33,46 +33,3 @@ if uploaded_file:
 
 else:
     st.write("Upload an image to start classification.")
-
-from io import BytesIO
-from fastai.vision.all import *
-#from fastai.vision.all import load_learner
-
-# Initialize Streamlit app
-st.title("White Blood Cell Classifier")
-
-
-# Load the FastAI model for WBC identification
-fastai_model = load_learner('model1.pkl')
-
-# File uploader for image input
-uploaded_file = st.file_uploader("Upload an image for detection", type=["jpg", "png"])
-
-if uploaded_file:
-    # Open the uploaded image
-    image = Image.open(uploaded_file)
-    
-    # Perform inference
-    results = model.predict(np.array(image))
-    
-    # Display results
-    st.image(image, caption="Uploaded Image", use_column_width=True)
-    
-    # Render detection results
-    rendered_image = render_result(model=model, image=image, result=results[0])
-    
-    # Show the rendered result
-    st.image(rendered_image, caption="Detection Results", use_column_width=True)
-    
-   
-
-    # Display the counts of each cell type
-    st.write("Cell Type :")
-        # Perform inference with the FastAI model
-    pred, idx, probs = fastai_model.predict(image)
-    st.write("White Blood Cell Classification:")
-    categories = ('EOSINOPHIL', 'LYMPHOCYTE', 'MONOCYTE', 'NEUTROPHIL')
-    results_dict = dict(zip(categories, map(float, probs)))
-    st.write(results_dict)
-else:
-    st.write("Upload an image to start detection.")