cats vs dogs space

app.py

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+import gradio as gr
+import cv2
+from huggingface_hub import from_pretrained_keras
+from skimage import io
+
+ROWS, COLS = 150, 150
+
+model = from_pretrained_keras("carlosaguayo/cats_vs_dogs")
+
+def process_image(img):
+  img = cv2.resize(img, (ROWS, COLS), interpolation=cv2.INTER_CUBIC)
+  img = img / 255.0
+  img = img.reshape(1,ROWS,COLS,3)
+
+  prediction = model.predict(img)[0][0]
+  if prediction >= 0.5:
+      message = 'I am {:.2%} sure this is a Cat'.format(prediction)
+  else: 
+      message = 'I am {:.2%} sure this is a Dog'.format(1-prediction)
+  return message
+
+title = "Interactive demo: Classify cat vs dog"
+description = "Simple Cat vs Dog classification"
+article = ""
+# examples =[["image_0.png"], ["image_1.png"], ["image_2.png"]]
+
+iface = gr.Interface(fn=process_image, 
+                     inputs=gr.inputs.Image(), 
+                     outputs=gr.outputs.Textbox(),
+                     title=title,
+                     description=description)
+                    #  article=article,
+                    #  examples=examples)
+iface.launch()

packages.txt

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+python3-opencv

requirements.txt

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+gradio
+transformers
+opencv-python
+scikit-image
+tensorflow