Delete deployment

deployment/gradio/app.py

@@ -1,41 +0,0 @@
-import gradio as gr
-from src.infer import inference_pipeline
-
-# model_path = "checkpoints/ckpt_23_10_2025/best_cat_dog_classifier_model_20251019_122336.pth"
-
-
-def classify_image(
-        image_path: str
-) -> str:
-    """
-    Classify the input image as cat or dog.
-    """
-    if image_path is None:
-        return "Please upload an image."
-    try:
-        prediction = inference_pipeline(
-            image_path=image_path, 
-            model_path=model_path,
-            hf=True
-        )
-        return f"Prediction: {prediction.capitalize()}"
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🐶🐱 Cat vs Dog Classifier")
-
-    with gr.Row():
-        with gr.Column():
-            image_input = gr.Image(
-                type="filepath", 
-                label="Input"
-            )
-            classify_button = gr.Button("🔍 Classify")
-        with gr.Column():
-            output_text = gr.Textbox(label="🧠 Prediction", placeholder="Result will appear here")
-
-    classify_button.click(fn=classify_image, inputs=[image_input], outputs=[output_text])
-
-demo.launch(debug=True)
-