trained model, examples & app

app.py

@@ -1,7 +1,32 @@
-import gradio as gr
-
-def greet(name):
-    return "Hello " + name + "!!"
-
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+from fastai.vision import *
+from fastai.learner import load_learner
+from PIL import Image
+import gradio as gr
+
+image = Image.open("examples/riku.jpg")
+image.thumbnail((512,512))
+image
+
+learn = load_learner("model.pkl")
+categories = list(learn.dls.vocab)
+
+
+result,_,probs = learn.predict(image)
+print(f"This is a: {result}")
+print(f"Probability it's a {result}: {probs[categories.index(result)] * 100:.02f}%")
+
+def classify_image(img):
+    pred, ix, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+print(classify_image(image))
+
+# Whats the gradio input type? Image
+image = gr.inputs.Image(shape=(192,192))
+# Whats the gradio output type? Label
+label = gr.outputs.Label()
+# Set up some examples
+examples = ["examples/kairi.jpg", "examples/riku.jpg", "examples/sora.jpg"]
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:114d2aedff2138e929a95274626586f15e8691460a67acd82f89bd71c4749f7f
+size 46971417