Create app.py

app.py

@@ -0,0 +1,31 @@
+import timm
+import wandb
+import gradio as gr
+from pathlib import Path
+from fastai.vision.all import load_learner
+
+wandb.login(key='4d2ff70f59f0bfc0397e9fea4300819244bf3fce')
+wandb.init(
+    name='pepper_fastai_gradio',
+    project='plant_disease_detection',
+    entity='jumashafara',
+)
+
+categories = ['bacterial_spot', 'healthy']
+
+learner = load_learner(Path('pepper_fastai_model.pkl'))
+
+def classify(img):
+    category, index, probs = learner.predict(img)
+    return (dict(zip(categories, map(float, probs))))
+
+image = gr.inputs.Image(shape=(224))
+label = gr.outputs.Label()
+example = []
+
+interface = gr.Interface(fn=classify, 
+                         inputs='image', 
+                         outputs='label',
+                         example=example)
+
+interface.launch()