Update app

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.pkl filter=lfs diff=lfs merge=lfs -text

app.py

@@ -2,16 +2,30 @@
 My first gradio application, used to practice the deployment of a deep learning model
 """
 import gradio as gr
+from fastai.vision.all import *
 
 
-def greet(name):
-    """
-    Returns a welcome message
-    """
-    return "Hello " + name + "!!"
+learn = load_learner('model.pkl')
+devonian_invertebrates = (
+    "Agnostida",
+    "Ammonites",
+    "Brachiopods",
+    "Bryozoa",
+    "Cephalopods",
+    "Corals",
+    "Crinoids",
+    "Gastropods",
+    "Nautiloids",
+    "Trilobites",
+)
 
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")  # An example of how to use Gradio to create a simple
-# text to text interface with a function, the inputs and outputs can be represented as different things as seen in
-# the gradio documentation
-iface.launch()
+def classify_image(image):
+    _,_,probs = learn.predict(image)
+    return dict(zip(devonian_invertebrates, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+
+interface = gr.Interface(fn=classify_image, inputs=image, outputs=label).launch(inline=False)