Update README.md

README.md

@@ -1,3 +1,116 @@
----
-license: mit
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+# Scene Graph Generator API
+
+This repository provides an API endpoint for generating scene graphs from images. Upload an image, and the API returns the annotated image, a visual graph representation, and the detected relationships between objects.
+
+## API Usage
+
+### Endpoint
+
+```
+POST https://dixisouls-scene-graph-generator.hf.space/generate
+```
+
+### Parameters
+
+- `image`: The image file to analyze (multipart/form-data)
+- `confidence_threshold`: A value between 0 and 1 (default: 0.5)
+- `use_fixed_boxes`: Boolean value (default: false)
+
+### Response
+
+The API returns a JSON response with:
+
+```json
+{
+  "objects": [
+    {
+      "label": "person",
+      "label_id": 1,
+      "score": 0.91,
+      "bbox": [0.3, 0.4, 0.1, 0.3]
+    },
+    ...
+  ],
+  "relationships": [
+    {
+      "subject": "person",
+      "predicate": "riding",
+      "object": "bicycle",
+      "score": 0.82,
+      "subject_id": 0,
+      "object_id": 1,
+      "predicate_id": 5
+    },
+    ...
+  ],
+  "annotated_image": "base64_encoded_image_data",
+  "graph_image": "base64_encoded_image_data"
+}
+```
+
+## Example Usage
+
+### Python
+
+```python
+import requests
+import base64
+from PIL import Image
+import io
+
+# Prepare the image
+image_path = "your_image.jpg"
+files = {'image': open(image_path, 'rb')}
+
+# Set parameters
+data = {
+    'confidence_threshold': 0.5,
+    'use_fixed_boxes': False
+}
+
+# Make the API call
+api_url = "https://dixisouls-scene-graph-generator.hf.space/generate"
+response = requests.post(api_url, files=files, data=data)
+
+# Process the results
+if response.status_code == 200:
+    result = response.json()
+    
+    # Decode and save the images
+    annotated_image = Image.open(io.BytesIO(base64.b64decode(result['annotated_image'])))
+    annotated_image.save("annotated_image.jpg")
+    
+    graph_image = Image.open(io.BytesIO(base64.b64decode(result['graph_image'])))
+    graph_image.save("graph_image.jpg")
+    
+    # Print information about objects and relationships
+    print(f"Found {len(result['objects'])} objects and {len(result['relationships'])} relationships")
+else:
+    print(f"Error: {response.text}")
+```
+
+### cURL
+
+```bash
+curl -X POST \
+  -F "image=@your_image.jpg" \
+  -F "confidence_threshold=0.5" \
+  -F "use_fixed_boxes=false" \
+  https://dixisouls-scene-graph-generator.hf.space/generate
+```
+
+## Model Information
+
+This API uses:
+
+- YOLOv8 for object detection
+- A custom neural network for relationship prediction
+- PyTorch as the deep learning framework
+
+## License
+
+This project is licensed under the MIT License.
+
+## Author
+
+Created by [dixisouls](https://github.com/dixisouls)