gradio

app.py

@@ -1,22 +1,18 @@
-import streamlit as st
+import gradio as gr
 from fastai.learner import load_learner
 from fastai.vision.core import PILImage
 from huggingface_hub import hf_hub_download
 
 
-st.title("Fastai Image Classifier")
-
 learner = load_learner(hf_hub_download("jdmartinev/intel_image_classification_fastai","model.pkl"))
 
-uploaded_img = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
-
-
-if uploaded_img:
-    st.image(uploaded_img, caption="Uploaded Image", use_column_width=True)
-    img = PILImage.create(uploaded_img)
-    
-    # Make predictions
-    pred_class, pred_idx, outputs = learner.predict(img)
-    st.write(f"Predicted class: {pred_class}")
+def classify_image(image):
+    img = PILImage.create(image)
+    pred_class, pred_idx, outputs = learn.predict(img)
+    return f"Predicted class: {pred_class}"
 
+interface = gr.Interface(fn=classify_image, 
+                         inputs=gr.inputs.Image(type="file", label="Upload an Image"), 
+                         outputs="text")
 
+interface.launch()

requirements.txt

@@ -1,2 +1,2 @@
-streamlit
+gradio
 fastai