Initialize hf-space

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,14 @@
+---
+title: Mlops Labs 1 3
+emoji: 🦀
+colorFrom: yellow
+colorTo: red
+sdk: gradio
+sdk_version: 6.0.1
+app_file: app.py
+pinned: false
+license: mit
+short_description: code developed across Labs 1–3 of an MLOps course
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,81 @@
+import gradio as gr
+import requests
+
+# URL of the API created with FastAPI
+API_URL = "https://mlops-lab2-frdj.onrender.com"
+
+# Function to predict image class
+def predict_image(image, class_names):
+    try:
+        # Save image to bytes
+        import io
+        from PIL import Image
+        
+        img_byte_arr = io.BytesIO()
+        image.save(img_byte_arr, format='PNG')
+        img_byte_arr.seek(0)
+        
+        # Prepare the request
+        files = {"file": ("image.png", img_byte_arr, "image/png")}
+        data = {"class_names": class_names}
+        
+        response = requests.post(f"{API_URL}/predict", files=files, data=data, timeout=10)
+        response.raise_for_status()
+        result = response.json()
+        return result.get("predicted_class")
+    except requests.exceptions.HTTPError as e:
+        return f"Error: {response.json().get('detail', str(e))}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function to resize image
+def resize_image(image, width, height):
+    try:
+        import io
+        
+        img_byte_arr = io.BytesIO()
+        image.save(img_byte_arr, format='PNG')
+        img_byte_arr.seek(0)
+        
+        files = {"file": ("image.png", img_byte_arr, "image/png")}
+        data = {"width": int(width), "height": int(height)}
+        
+        response = requests.post(f"{API_URL}/resize", files=files, data=data, timeout=10)
+        response.raise_for_status()
+        result = response.json()
+        return str(result.get("resized_dimensions"))
+    except requests.exceptions.HTTPError as e:
+        return f"Error: {response.json().get('detail', str(e))}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# GUI created using Gradio with Tabs
+with gr.Blocks() as iface:
+    gr.Markdown("# Image Classifier and Resizer")
+    
+    with gr.Tab("Predict"):
+        with gr.Row():
+            img_input = gr.Image(type="pil", label="Upload Image")
+        class_input = gr.Textbox(
+            value="cardboard,paper,plastic,metal,trash,glass",
+            label="Class Names (comma-separated)"
+        )
+        predict_btn = gr.Button("Predict")
+        predict_output = gr.Textbox(label="Predicted Class")
+        
+        predict_btn.click(predict_image, inputs=[img_input, class_input], outputs=predict_output)
+    
+    with gr.Tab("Resize"):
+        with gr.Row():
+            img_resize = gr.Image(type="pil", label="Upload Image")
+        with gr.Row():
+            width_input = gr.Number(value=256, label="Width")
+            height_input = gr.Number(value=256, label="Height")
+        resize_btn = gr.Button("Resize")
+        resize_output = gr.Textbox(label="New Dimensions")
+        
+        resize_btn.click(resize_image, inputs=[img_resize, width_input, height_input], outputs=resize_output)
+
+# Launch the GUI
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1,2 @@
+gradio>=3.40
+requests>=2.30