Upload 2 files

app.py

@@ -0,0 +1,29 @@
+Crop_Disease_Identificationfrom fastai.vision.all import *
+from fastai.vision.all import load_learner
+import gradio as gr
+
+fruit_labels = ('Anthracnose', 'Apple Scab', 'Black Spot', 'Blight', 
+                'Blossom End Rot', 'Botrytis', 'Brown Rot', 'Canker', 
+                'Cedar Apple Rust', 'Clubroot', 'Crown Gall', 'Downy Mildew', 
+                'Fire Blight', 'Fusarium', 'Gray Mold', 'Leaf Spots', 'Mosaic Virus', 
+                'Nematodes', 'Powdery Mildew', 'Verticillium')
+
+model=load_learner("crop_model_1.pkl")
+
+def recognize_image(image):
+  pred, idx, probs = model.predict(image)
+  print(pred)
+  return dict(zip(fruit_labels, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label(num_top_classes=5)
+examples = [
+    'image_1.jpg',
+    'image_2.jpeg',
+    'image_3.jpeg',
+    'image_4.jpeg'
+]
+
+iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
+iface.launch(inline=False)

requirements.txt

@@ -0,0 +1,2 @@
+Gradio==3.50.0
+Fastai==2.7.13