first commit of NSFW classification

app.py

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+import gradio as gr
+import numpy as np
+import urllib
+from keras.preprocessing import image
+from keras.models import load_model
+
+# Load the pre-trained model
+model = load_model('my_model.h5')
+CATEGORIES = ("NSFW", "SFW")
+def classify_image(img):
+    # Preprocess the input image
+    img = image.img_to_array(img)
+    img = np.expand_dims(img, axis=0)
+    img /= 255.0
+    
+    # Use the model to make a prediction
+    prediction = model.predict(img)
+    print(prediction)
+    # Map the predicted class to a label
+    if prediction[0][0] >= 0.5:
+        label = "SFW"
+    else:
+        label = "NSFW"
+    
+    return label
+
+def classify_url(url):
+    # Load the image from the URL
+    response = urllib.request.urlopen(url)
+    img = image.load_img(response, target_size=(224, 224))
+    
+    return classify_image(img)
+
+# Define the GRADIO input interface
+#inputs = gr.inputs.Image(shape=(224, 224, 3))
+
+# Define the GRADIO output interface
+#outputs = gr.outputs.Textbox(lines=1, default="SFW")
+
+# Define the GRADIO app
+app = gr.Interface(classify_image, gr.Image(shape=(224, 224)), outputs=gr.Label(label="Type of Image"), allow_flagging="never", title="NSFW/SFW Classifier")
+
+# Start the GRADIO app
+app.launch()
+

my_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7117e488bc01eca0c8dbb644cafa4d7f0b0b559b873500e507ad2be32dd8d6a3
+size 2245216