Update app.py

app.py

@@ -1,55 +1,56 @@
-# '''PyTorch Food Classifier - FastAI 2022- Mostly Good For Pastries
-# and trained on ResNet 34'''
+'''PyTorch Food Classifier - FastAI 2022- Mostly Good For Pastries
+and trained on ResNet 34'''
 
-# import streamlit as st
-# import os
-# from PIL import Image
-# import time
-# from fastai.vision.all import *
-# from fastai.learner import load_learner
+import streamlit as st
+import os
+from PIL import Image
+import time
+from fastai.vision.all import *
+from fastai.learner import load_learner
 
-# def is_penguin(img):
-#     return img.split('-')[0]
+def is_penguin(img):
+    return img.split('-')[0]
     
-# #Load the Learner (Exported from ipnyb file with learn.export() )
-# learn = load_learner('model.pkl')
+#Load the Learner (Exported from ipnyb file with learn.export() )
+learn = load_learner('model.pkl')
 
-# categories = ('Penguin', 'Puffin')
+categories = ('Penguin', 'Puffin')
 
-# #Classify image
-# def classify_image(cl_img):
-#     img = Image.open(cl_img)
-#     st.image(img)
-#     pred, _ , prob = learn.predict(img)
-#     return dict(zip(categories, map(float, prob)))
+#Classify image
+def classify_image(cl_img):
+    img = Image.open(cl_img)
+    st.image(img)
+    pred, pred_idx, prob = learn.predict(img)
+    confidence = prob[pred_idx].item() * 100
+    return pred, prob
     
-# st.set_page_config(page_title="Penguin vs Puffin Classifier - FastAI 2025", page_icon=":robot:")
-# st.header("Penguin vs Puffin Classifier")
+st.set_page_config(page_title="Penguin vs Puffin Classifier - FastAI 2025", page_icon=":robot:")
+st.header("Penguin vs Puffin Classifier")
 
-# file_up = st.file_uploader("Upload Your Image Below", type=["jpg","png"])
+file_up = st.file_uploader("Upload Your Image Below", type=["jpg","png"])
 
-# if st.button('Run Model'):
-#     st.write("Button Pressed")
-#     cl_done = classify_image(file_up)
-#     st.write(f"Your food is:  {cl_done}")
+if st.button('Run Model'):
+    st.write("Button Pressed")
+    pred_label, confidence = classify_image(file_up)
+    st.write(f"The model predicts {pred_label} with {confidence} confidence.")
 
-# st.write('This classifier is trained on Resnet-34 and specializes in differentiating penguins from puffins).')
+st.write('This classifier is trained on Resnet-34 and specializes in differentiating penguins from puffins).')
 
-from fastai.vision.all import *
-from fastai.learner import load_learner
-import gradio as gr
+# from fastai.vision.all import *
+# from fastai.learner import load_learner
+# import gradio as gr
 
-learn = load_learner('model.pkl')
+# learn = load_learner('model.pkl')
 
-categories = ('Penguin', 'Puffin')
+# categories = ('Penguin', 'Puffin')
 
-def classifyImage(img):
-    pred, idx, prob = learn.predict(img)
-    return dict(zip(categories, map(float, prob)))
+# def classifyImage(img):
+#     pred, idx, prob = learn.predict(img)
+#     return dict(zip(categories, map(float, prob)))
 
-image = gr.Image(shape=(192, 192))
-label = gr.Label()
-examples = ['penguin.jpg', 'puffin.png', 'razorbill.jpg']
+# image = gr.Image(shape=(192, 192))
+# label = gr.Label()
+# examples = ['penguin.jpg', 'puffin.png', 'razorbill.jpg']
 
-intf = gr.Interface(fn=classifyImage, inputs=image, outputs=label, examples=examples)
-intf.launch(inline=False)
+# intf = gr.Interface(fn=classifyImage, inputs=image, outputs=label, examples=examples)
+# intf.launch(inline=False)