chore: adding demo

.gitattributes

@@ -33,3 +33,4 @@ 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

app.py

@@ -0,0 +1,189 @@
+import gradio as gr
+from transformers import pipeline
+from transformers.image_utils import load_image
+
+checkpoints = [
+    'ustc-community/dfine_n_coco',
+    'ustc-community/dfine_s_coco',
+    'ustc-community/dfine_m_coco',
+    'ustc-community/dfine_l_coco',
+    'ustc-community/dfine_x_coco',
+    'ustc-community/dfine_s_obj365',
+    'ustc-community/dfine_m_obj365',
+    'ustc-community/dfine_l_obj365',
+    'ustc-community/dfine_x_obj365',
+    'ustc-community/dfine_s_obj2coco',
+    'ustc-community/dfine_m_obj2coco',
+    'ustc-community/dfine_l_obj2coco_e25',
+    'ustc-community/dfine_x_obj2coco',
+]
+
+def detect_objects(image, checkpoint, confidence_threshold=0.3, use_url=False, url=""):
+    pipe = pipeline(
+        "object-detection",
+        model=checkpoint,
+        image_processor=checkpoint,
+        device="cpu",
+    )
+
+    if use_url and url:
+        input_image = load_image(url)
+    elif image is not None:
+        input_image = image
+    else:
+        return None, gr.Markdown("**Error**: Please provide an image or URL.", visible=True)
+
+    # Run detection
+    results = pipe(input_image, threshold=confidence_threshold)
+
+    # Get image dimensions for validation
+    img_width, img_height = input_image.size
+
+    # Prepare annotations in the format: list of (bounding_box, label)
+    annotations = []
+    for result in results:
+        score = result["score"]
+        if score < confidence_threshold:
+            continue
+        label = f"{result['label']} ({score:.2f})"
+        box = result["box"]
+        # Validate and convert box to (x1, y1, x2, y2)
+        x1 = max(0, int(box["xmin"]))
+        y1 = max(0, int(box["ymin"]))
+        x2 = min(img_width, int(box["xmax"]))
+        y2 = min(img_height, int(box["ymax"]))
+        # Ensure valid box
+        if x2 <= x1 or y2 <= y1:
+            continue
+        bounding_box = (x1, y1, x2, y2)
+        annotations.append((bounding_box, label))
+
+    # Handle empty annotations
+    if not annotations:
+        return (input_image, []), gr.Markdown(
+            "**Warning**: No objects detected above the confidence threshold. Try lowering the threshold.",
+            visible=True
+        )
+
+    # Return base image and annotations
+    return (input_image, annotations), gr.Markdown(visible=False)
+
+# Gradio interface
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # Real-Time Object Detection Demo
+        Experience state-of-the-art object detection with USTC's Dfine models. Upload an image, provide a URL, or try an example below. Select a model and adjust the confidence threshold to see detections in real time!
+
+        **Instructions**:
+        - Upload an image or enter a URL.
+        - Choose a model checkpoint from the dropdown.
+        - Adjust the confidence threshold (0.1 to 1.0).
+        - Click "Detect Objects" to view results, or select an example.
+        - Use "Clear" to reset inputs and outputs.
+        """,
+        elem_classes="header-text"
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=1, min_width=300):
+            with gr.Group():
+                image_input = gr.Image(
+                    label="Upload Image",
+                    type="pil",
+                    sources=["upload", "webcam"],
+                    interactive=True,
+                    elem_classes="input-component",
+                )
+                use_url = gr.Checkbox(label="Use Image URL Instead", value=False)
+                url_input = gr.Textbox(
+                    label="Image URL",
+                    placeholder="https://example.com/image.jpg",
+                    visible=False,
+                    elem_classes="input-component",
+                )
+                checkpoint = gr.Dropdown(
+                    choices=checkpoints,
+                    label="Select Model Checkpoint",
+                    value=checkpoints[0],
+                    elem_classes="input-component",
+                )
+                confidence_threshold = gr.Slider(
+                    minimum=0.1,
+                    maximum=1.0,
+                    value=0.3,
+                    step=0.1,
+                    label="Confidence Threshold",
+                    elem_classes="input-component",
+                )
+                with gr.Row():
+                    detect_button = gr.Button(
+                        "Detect Objects",
+                        variant="primary",
+                        elem_classes="action-button",
+                    )
+                    clear_button = gr.Button(
+                        "Clear",
+                        variant="secondary",
+                        elem_classes="action-button",
+                    )
+        
+        with gr.Column(scale=2):
+            output_annotated = gr.AnnotatedImage(
+                label="Detection Results",
+                show_label=True,
+                color_map=None,  # Let Gradio assign colors
+                elem_classes="output-component",
+            )
+            error_message = gr.Markdown(visible=False, elem_classes="error-text")
+    
+    gr.Examples(
+        examples=[
+            ["./image.jpg", False, "", checkpoints[0], 0.3],
+            [None, True, "https://live.staticflickr.com/65535/33021460783_1646d43c54_b.jpg", checkpoints[0], 0.3],
+        ],
+        inputs=[image_input, use_url, url_input, checkpoint, confidence_threshold],
+        outputs=[output_annotated, error_message],
+        fn=detect_objects,
+        cache_examples=False,  # Avoid caching due to model size
+        label="Select an example to run the model",
+    )
+
+    # Dynamic visibility for URL input
+    use_url.change(
+        fn=lambda x: gr.update(visible=x),
+        inputs=use_url,
+        outputs=url_input,
+    )
+
+    # Clear button functionality
+    clear_button.click(
+        fn=lambda: (
+            None,  # image_input
+            False,  # use_url
+            "",  # url_input
+            checkpoints[0],  # checkpoint
+            0.3,  # confidence_threshold
+            None,  # output_annotated
+            gr.Markdown(visible=False),  # error_message
+        ),
+        outputs=[
+            image_input,
+            use_url,
+            url_input,
+            checkpoint,
+            confidence_threshold,
+            output_annotated,
+            error_message,
+        ],
+    )
+
+    # Detect button event
+    detect_button.click(
+        fn=detect_objects,
+        inputs=[image_input, checkpoint, confidence_threshold, use_url, url_input],
+        outputs=[output_annotated, error_message],
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,63 @@
+aiofiles==24.1.0
+annotated-types==0.7.0
+anyio==4.9.0
+certifi==2025.4.26
+charset-normalizer==3.4.1
+click==8.1.8
+fastapi==0.115.12
+ffmpy==0.5.0
+filelock==3.18.0
+fsspec==2025.3.2
+gradio==5.28.0
+gradio-client==1.10.0
+groovy==0.1.2
+h11==0.16.0
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==0.30.2
+idna==3.10
+jinja2==3.1.6
+markdown-it-py==3.0.0
+markupsafe==3.0.2
+mdurl==0.1.2
+mpmath==1.3.0
+networkx==3.4.2
+numpy==2.2.5
+orjson==3.10.18
+packaging==25.0
+pandas==2.2.3
+pillow==11.2.1
+pydantic==2.11.4
+pydantic-core==2.33.2
+pydub==0.25.1
+pygments==2.19.1
+python-dateutil==2.9.0.post0
+python-multipart==0.0.20
+pytz==2025.2
+pyyaml==6.0.2
+regex==2024.11.6
+requests==2.32.3
+rich==14.0.0
+ruff==0.11.8
+safehttpx==0.1.6
+safetensors==0.5.3
+semantic-version==2.10.0
+setuptools==80.1.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+starlette==0.46.2
+sympy==1.14.0
+tokenizers==0.21.1
+tomlkit==0.13.2
+torch==2.7.0
+torchvision==0.22.0
+tqdm==4.67.1
+transformers @ git+https://github.com/huggingface/transformers@ee25d57ed18f2dc06e88bd041830c6a32f80ff88
+typer==0.15.3
+typing-extensions==4.13.2
+typing-inspection==0.4.0
+tzdata==2025.2
+urllib3==2.4.0
+uvicorn==0.34.2
+websockets==15.0.1