Update app.py

app.py

@@ -1,50 +1,38 @@
-## import gradio as gr
-#
-## def greet(name):
-##     return "Hello " + name + "!!"
-#
-## iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-## iface.launch()
-
 import gradio as gr
 from fastai.vision.all import *
-import skimage
 import pathlib
+
+# Adjust the path handling for compatibility between different OS
 temp = pathlib.PosixPath
 pathlib.PosixPath = pathlib.WindowsPath
 pathlib.PosixPath = temp
 
+# Load your pre-trained model
 learn = load_learner('model.pkl')
 labels = learn.dls.vocab
+
+# Prediction function
 def predict(img):
    img = PILImage.create(img)
-   pred,pred_idx,probs = learn.predict(img)
+   pred, pred_idx, probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
+# Title and description
 title = "Female/Male Classifier"
 description = "A Female/Male classifier trained on the duckduckgo search result with fastai. Created as a demo for Gradio and HuggingFace Spaces."
-## article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
-examples = ['femaleDefault.jpg', 'maleDefault.jpg',
-       'dragQueen1.jpg', 'dragQueen2.jpg',
-       'femaleAngry1.jpg', 'femaleAngry2.jpg',
-       'femaleMuscle1.jpg', 'femaleMuscle2.jpg',
-       'maleAsian.jpg', 'maleEurope.jpg',
-       'femaleAsian.jpg', 'femaleDefault.jpg',
-       'maleCrying2.jpg', 'maleCrying2No.jpg']
-#interpretation='default'
-enable_queue=True
-#
-## gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
-#
+examples = ['femaleDefault.jpg', 'maleDefault.jpg', 'dragQueen1.jpg', 'dragQueen2.jpg', 'femaleAngry1.jpg', 'femaleAngry2.jpg', 'femaleMuscle1.jpg', 'femaleMuscle2.jpg', 'maleAsian.jpg', 'maleEurope.jpg', 'femaleAsian.jpg', 'femaleDefault.jpg', 'maleCrying2.jpg', 'maleCrying2No.jpg']
+
+# Update the Gradio Interface without using deprecated arguments
 inter = gr.Interface(
    fn=predict,
-   inputs=gr.Image(shape=(512, 512)),
-   outputs=gr.outputs.Label(),
+   inputs=gr.Image(type="pil", shape=(512, 512)),  # "type='pil'" specifies the image type
+   outputs=gr.Label(),
    title=title,
    description=description,
    examples=examples,
    cache_examples=True,
-   examples_per_page=2)
+   examples_per_page=2
+)
 
 inter.queue()
-inter.launch()
+inter.launch()