Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from fastai.vision.all import *
 import skimage
 
-learn = load_learner('modelo18.pkl')
+learn = load_learner('modelo50.pkl')
 
 labels = learn.dls.vocab
 def predict(img):
@@ -10,11 +10,11 @@ def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-title = "Bleach - Qual potencial de guerra?"
+title = "Bleach - Qual potencial de guerra? - RestNet50"
 description = "Reconhecer os 5 Potenciais (Bleach)"
 examples = ['Aizen.jpg', 'Ichigo.jpg', 'Zaraki.jpg','Ichibe.jpg', 'Urahara.jpg']
-interpretation='default'
-enable_queue=True
+interpretation ='default'
+enable_queue = True
 
 gr.Interface(fn=predict,
              inputs=gr.inputs.Image(shape=(512, 512)),
@@ -23,54 +23,4 @@ gr.Interface(fn=predict,
              description=description,
              examples=examples,
              interpretation=interpretation,
-             enable_queue=enable_queue).launch()
-
-#////////////////////////////////////////////////////////////////////////////////////////////////
-
-learn02 = load_learner('modelo34.pkl')
-
-labels2 = learn.dls.vocab
-def predict(img):
-    img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
-    return {labels2[i]: float(probs[i]) for i in range(len(labels2))}
-
-title2 = "Bleach - Qual potencial de guerra?"
-description2 = "Reconhecer os 5 Potenciais (Bleach)"
-examples2 = ['Aizen.jpg', 'Ichigo.jpg', 'Zaraki.jpg','Ichibe.jpg', 'Urahara.jpg']
-interpretation2='default'
-enable_queue2 = True
-
-gr.Interface2(fn=predict,
-             inputs=gr.inputs.Image(shape=(512, 512)),
-             outputs=gr.outputs.Label(num_top_classes=3),
-             title=title2,
-             description=description2,
-             examples=examples2,
-             interpretation=interpretation2,
-             enable_queue=enable_queue2).launch()
-
-#////////////////////////////////////////////////////////////////////////////////////////////////
-
-learn03 = load_learner('modelo50.pkl')
-
-labels3 = learn.dls.vocab
-def predict(img):
-    img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
-    return {labels3[i]: float(probs[i]) for i in range(len(labels3))}
-
-title3 = "Bleach - Qual potencial de guerra?"
-description3 = "Reconhecer os 5 Potenciais (Bleach)"
-examples3 = ['Aizen.jpg', 'Ichigo.jpg', 'Zaraki.jpg','Ichibe.jpg', 'Urahara.jpg']
-interpretation3='default'
-enable_queue3 = True
-
-gr.Interface3(fn=predict,
-             inputs=gr.inputs.Image(shape=(512, 512)),
-             outputs=gr.outputs.Label(num_top_classes=3),
-             title=title3,
-             description=description3,
-             examples=examples3,
-             interpretation=interpretation3,
-             enable_queue=enable_queue3).launch()
+             enable_queue=enable_queue).launch()