gradio

app - Copy.py

@@ -0,0 +1,23 @@
+import gradio as gr
+from fastai.vision.all import *
+import pathlib
+
+plt = platform.system()
+if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
+
+learn = load_learner('YomeRecognition.pkl')
+
+labels = learn.dls.vocab # list of model classes
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=5),
+    title="😍 Sugar 🐶 Yome 🦮 Yang Chenchen 💕 Recognition 🐕",
+    description="Classifier trainded on images of Yang Chenchen Yome, Wang Xinyao, and others. ",
+    examples=['jpg/a.jpg', 'jpg/b.jpg', 'jpg/c.jpg',  'jpg/1.jpg', 'jpg/2.jpg', 'jpg/4.jpg', 'jpg/5.jpg', 'jpg/6.jpg', 'jpg/9.jpg'],
+    enable_queue=True).launch()

app.py

@@ -8,16 +8,24 @@ if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
 learn = load_learner('YomeRecognition.pkl')
 
 labels = learn.dls.vocab # list of model classes
-def predict(img):
-    img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
-    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+# def predict(img):
+#     img = PILImage.create(img)
+#     pred,pred_idx,probs = learn.predict(img)
+#     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-gr.Interface(
-    fn=predict,
-    inputs=gr.inputs.Image(shape=(512, 512)),
-    outputs=gr.outputs.Label(num_top_classes=5),
-    title="😍 Sugar 🐶 Yome 🦮 Yang Chenchen 💕 Recognition 🐕",
-    description="Classifier trainded on images of Yang Chenchen Yome, Wang Xinyao, and others. ",
-    examples=['a.jpg', 'b.jpg', 'c.jpg',  '1.jpg', '2.jpg', '4.jpg', '5.jpg', '6.jpg', '9.jpg'],
-    enable_queue=True).launch()
+# gr.Interface(
+#     fn=predict,
+#     inputs=gr.inputs.Image(shape=(512, 512)),
+#     outputs=gr.outputs.Label(num_top_classes=5),
+#     title="😍 Sugar 🐶 Yome 🦮 Yang Chenchen 💕 Recognition 🐕",
+#     description="Classifier trainded on images of Yang Chenchen Yome, Wang Xinyao, and others. ",
+#     examples=['jpg/a.jpg', 'jpg/b.jpg', 'jpg/c.jpg',  'jpg/1.jpg', 'jpg/2.jpg', 'jpg/4.jpg', 'jpg/5.jpg', 'jpg/6.jpg', 'jpg/9.jpg'],
+#     enable_queue=True).launch()
+    
+    
+
+def greet(name):
+    return "Hello " + name + "!!"
+
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()