Add app and sample images, track images with LFS

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* 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
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+.env 

app.py

@@ -0,0 +1,113 @@
+import spaces
+import gradio as gr
+import os
+from dotenv import load_dotenv
+from ultralytics import YOLO
+import cv2
+import numpy as np
+from PIL import Image
+from huggingface_hub import hf_hub_download
+
+# Load environment variables
+load_dotenv()
+
+# Get model repo and filename from environment variable
+MODEL_REPO = os.getenv("MODEL_REPO", "visionNoob/test_model")
+MODEL_FILENAME = os.getenv("MODEL_FILENAME", "weights/best.pt")
+HF_TOKEN = os.getenv("HF_TOKEN")
+SECRET_KEY = os.getenv("SECRET_KEY", "changeme")
+
+# Download model from Hugging Face Hub
+model_path = hf_hub_download(
+    repo_id=MODEL_REPO, filename=MODEL_FILENAME, token=HF_TOKEN
+)
+print(f"Model downloaded to: {model_path}")
+# Load YOLO model
+model = YOLO(model_path)
+
+
+@spaces.GPU
+def predict(image):
+    """
+    Predict objects in the input image using YOLO model (YOLOv11x)
+    """
+    if image is None:
+        return None
+
+    # Run inference
+    results = model(image)
+
+    # Get the first result (assuming single image)
+    result = results[0]
+
+    # Draw bounding boxes on the image
+    annotated_image = result.plot()
+
+    # Convert BGR to RGB for display
+    annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
+
+    return Image.fromarray(annotated_image)
+
+
+# --- Authentication logic ---
+def check_secret_key(input_key):
+    if input_key == SECRET_KEY:
+        return gr.update(visible=False), gr.update(visible=True), ""
+    else:
+        return (
+            gr.update(visible=True),
+            gr.update(visible=False),
+            "Incorrect password. Please try again.",
+        )
+
+
+# Authentication components
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    with gr.Group(visible=True) as auth_ui:
+        gr.Markdown("# Authentication Required: Enter SECRET_KEY")
+        secret_input = gr.Textbox(
+            type="password", label="Enter SECRET_KEY", interactive=True
+        )
+        submit_btn = gr.Button("Confirm")
+        error_text = gr.Markdown(visible=False)
+
+    # Main interface (hidden by default)
+    with gr.Column(visible=False) as main_ui:
+        gr.Interface(
+            fn=predict,
+            inputs=gr.Image(type="pil", label="Upload Image"),
+            outputs=gr.Image(type="pil", label="Predictions"),
+            title="TRASH-10 Object Detection (YOLOv11x)",
+            examples=[
+                "samples/sample1.jpg",
+                "samples/sample2.jpg",
+                "samples/sample3.jpg",
+                "samples/sample4.jpg",
+                "samples/sample5.jpg",
+                "samples/sample6.jpg",
+            ],
+        )
+
+    def handle_secret_key(input_key):
+        if input_key == SECRET_KEY:
+            # Hide auth UI, show main, hide error
+            return (
+                gr.update(visible=False),
+                gr.update(visible=True),
+                gr.update(visible=False),
+            )
+        else:
+            # Show auth UI, hide main, show error
+            return (
+                gr.update(visible=True),
+                gr.update(visible=False),
+                gr.update(visible=True, value="Incorrect password. Please try again."),
+            )
+
+    submit_btn.click(
+        handle_secret_key,
+        inputs=secret_input,
+        outputs=[auth_ui, main_ui, error_text],
+    )
+
+demo.launch()