new file: app.py

new file: requirements.txt

app.py

@@ -0,0 +1,31 @@
+import opennsfw2
+import numpy as np
+import gradio as gr
+
+
+def predict_nsfw(pil_image) -> str:
+    image = opennsfw2.preprocess_image(
+        pil_image, opennsfw2.Preprocessing.YAHOO)
+
+    model = opennsfw2.make_open_nsfw_model()
+
+    # Add batch axis (for single image).
+    inputs = np.expand_dims(image, axis=0)
+
+    predictions = model.predict(inputs)
+
+    # The shape of predictions is (num_images, 2).
+    sfw_probability, nsfw_probability = predictions[0]
+    if nsfw_probability > sfw_probability:
+        result_str = f"It is NSFW image.\nnsfw_probability: {nsfw_probability:.5f}"
+    else:
+        result_str = f"It is NOT NSFW image.\nnsfw_probability: {nsfw_probability:.5f}"
+    return result_str
+
+
+inputs = gr.inputs.Image(label="input_image", type="pil")
+outputs = gr.outputs.Textbox(label="output_string")
+
+app = gr.Interface(fn=predict_nsfw, inputs=inputs, outputs=outputs)
+
+app.launch()

requirements.txt

@@ -0,0 +1,9 @@
+gdown>=4.2.0
+matplotlib>=3.0.0
+numpy>=1.22.0
+opencv-python>=4.0.0.0
+Pillow>=9.0.0
+scikit-image>=0.18.0
+tensorflow>=2.0.0
+tqdm>=4.62
+opennsfw2