working model

README.md

@@ -1,12 +1,22 @@
 ---
 title: Mona Lisa Detection
-emoji: 💻
-colorFrom: indigo
-colorTo: yellow
+emoji: 🖼
+colorFrom: white
+colorTo: white
 sdk: gradio
 sdk_version: 3.19.1
 app_file: app.py
 pinned: false
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+## Setup + Run
+```bash
+virtualenv .venv
+source .venv/bin/activate 
+pip install -r requirements.txt
+python app.py
+
+```

app.py

@@ -0,0 +1,56 @@
+import pathlib
+import gradio as gr
+from loguru import logger
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+logger.info("starting gradio app")
+
+CURRENT_DIR = pathlib.Path(__file__).resolve().parent
+APP_NAME = "Mona Lisa Detection"
+
+logger.debug("loading processor and model.")
+processor = AutoFeatureExtractor.from_pretrained(
+    "drift-ai/autotrain-mona-lisa-detection-38345101350"
+)
+model = AutoModelForImageClassification.from_pretrained(
+    "drift-ai/autotrain-mona-lisa-detection-38345101350"
+)
+logger.debug("loading processor and model succeeded.")
+
+
+def process_image(image, model=model, processor=processor):
+    logger.info("Making a prediction ...")
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    result = model.config.id2label[predicted_class_idx]
+    print("Predicted class:", result)
+    logger.info("Prediction finished.")
+    return result
+
+
+examples = [
+    "mona-lisa-1.jpg",
+    "mona-lisa-2.jpg",
+    "mona-lisa-3.jpg",
+    "not-mona-lisa-1.jpg",
+    "not-mona-lisa-2.jpg",
+    "not-mona-lisa-3.jpg",
+]
+
+if __name__ == "__main__":
+    title = """
+        Mona Lisa Detection.
+"""
+    app = gr.Interface(
+        fn=process_image,
+        inputs=[
+            gr.inputs.Image(type="pil", label="Image"),
+        ],
+        outputs=gr.Label(label="Predictions:", show_label=True),
+        examples=examples,
+        examples_per_page=32,
+        title=title,
+        enable_queue=True,
+    ).launch()

requirements.txt

@@ -0,0 +1,4 @@
+loguru
+gradio
+transformers
+torch