Model Deployment

app.py

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+from ultralytics import YOLO
+from PIL import Image
+import gradio as gr
+from huggingface_hub import snapshot_download
+import os
+
+# 1) Change this to your model repo (you already have it)
+REPO_ID = "Interior-Style-Classification"
+WEIGHTS_FILENAME = "best.pt"   # file in your model repo
+
+def load_model(repo_id: str) -> YOLO:
+    """
+    Downloads the model repo from Hugging Face Hub into the Space cache
+    and loads the YOLO model from the weights file.
+    """
+    download_dir = snapshot_download(repo_id=repo_id)
+    weights_path = os.path.join(download_dir, WEIGHTS_FILENAME)
+
+    if not os.path.exists(weights_path):
+        raise FileNotFoundError(
+            f"Cannot find {WEIGHTS_FILENAME} inside downloaded repo: {download_dir}\n"
+            f"Files found: {os.listdir(download_dir)}"
+        )
+
+    return YOLO(weights_path, task="classify")
+
+classification_model = load_model(REPO_ID)
+
+def predict(pilimg: Image.Image) -> str:
+    results = classification_model.predict(pilimg)
+
+    probs = results[0].probs
+    class_id = probs.top1
+    confidence = probs.top1conf.item()
+    class_name = classification_model.names[class_id]
+
+    return f"{class_name} ({confidence:.2f})"
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload an interior image"),
+    outputs=gr.Textbox(label="Predicted interior style"),
+    title="Interior Style Classification (YOLOv8)",
+    description="Upload an image and the model will classify the interior design style."
+)
+
+demo.launch()