Upload app.py

app.py

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+#
+import fastai
+import fastai.vision
+import PIL
+import gradio
+import matplotlib
+import numpy
+import pandas
+from fastai.vision.all import *
+#
+learn = fastai.learner.load_learner('ada.pkl')
+categories = learn.dls.vocab
+def _predict_image(img):
+  pred,idx,probs = learn.predict(img)
+  return dict(zip(categories, map(float,probs)))
+image = gradio.inputs.Image(shape=(192, 192))
+label = gradio.outputs.Label()
+examples = ['dog1.jpg','dog2.jpg','dog3.jpg','dog4.jpg','dog5.png','dog6.jpg', 'dog7.jpg','duc.jpg']
+# from fancy up below (but don't do the canvas.show())
+def _draw_pred(df_pred):
+  canvas, pic = matplotlib.pyplot.subplots(1,1, figsize=(6,6))
+  ti = df_pred["breeds"].head(5).values
+  df_pred["pred"].head(5).plot(ax=pic,kind="pie",figsize=(6,6),
+    cmap="Set2",labels=ti)
+  t = str(ti[0]) + ": " + str(numpy.round(df_pred.head(1).pred.values[0]*100, 2)) + "% Certainty"
+  pic.set_title(t,fontsize=14.0, fontweight="bold")
+  pic.axis('off')
+  #
+  # draw circle
+  centre_circle = matplotlib.pyplot.Circle((0, 0), 0.6, fc='white')
+  canvas = matplotlib.pyplot.gcf()
+  # Adding Circle in Pie chart
+  canvas.gca().add_artist(centre_circle)
+  #
+  canvas.legend(ti, loc="lower right",title="120 Dog Breeds: Top 5")
+  #
+  canvas.tight_layout()
+  return canvas
+def predict_donut(img):
+  d = _predict_image(img)
+  df = pandas.DataFrame(d, index=[0])
+  df = df.transpose().reset_index()
+  df.columns = ["breeds", "pred"]
+  df.sort_values("pred", inplace=True,ascending=False, ignore_index=True)
+  canvas = _draw_pred(df)
+  return canvas
+art = '<br><ul><li>'
+art += 'Author: Duc Haba, 2022.</li>'
+art += '<li>https://linkedin.com/in/duchaba</li>'
+art += '<li>The training dataset is from the Data Scientist at Department of Health '
+art += 'and Social Care London, England, United Kingdom.</li>'
+art += '<li>https://www.kaggle.com/datasets/amandam1/120-dog-breeds-breed-classification</li>'
+art += '</ul>'
+intf = gradio.Interface(fn=predict_donut, 
+  inputs=image, 
+  outputs=["plot"], 
+  examples=examples,
+  title="120 Dog Breeds Prediction",
+  live=True,
+  article=art)
+intf.launch(inline=False,share=True)