updated app.py added example image files

app.py

@@ -1,7 +1,39 @@
+# import gradio as gr
+# 
+# def greet(name):
+#     return "Hello " + name + "!!"
+# 
+# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+# demo.launch(share=True)
+
+# AUTOGENERATED! DO NOT EDIT! File to edit: inference-face-crop-model.ipynb.
+
+# %% auto 0
+__all__ = ['learner', 'categories', 'classify_image']
+
+# %% inference-face-crop-model.ipynb 10
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+learner = load_learner('./face-crop-model.pkl')
+
+categories = ('happy', 'other')
+
+def classify_image(img):
+    img = img["composite"]
+    # print(img.shape)
+    img = img[:,:, :3]
+    pred, idx, probs = learner.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+with gr.Blocks() as demo:
+
+    image_edit = gr.ImageEditor(type="numpy", crop_size="1:1.2", canvas_size=(300, 300))
+        # image = gr.Image()
+    label = gr.Label()
+    examples = ['happy.png', "happy2.png", "happy3.png", "happy4.png", 'other.png', 'other2.png', 'other3.png', 'other4.png', 'other5.png',]
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+    intf = gr.Interface(fn=classify_image, inputs=image_edit, outputs=label, examples=examples,
+                       description="Use crop button to resize around the face for best results")
+# intf.launch(inline=False)
 demo.launch(share=True)