add readme

README.md

@@ -1,3 +1,71 @@
 ---
-license: mit
+tags:
+- ultralyticsplus
+- yolov5
+- ultralytics
+- yolo
+- vision
+- object-detection
+- pytorch
+- awesome-yolov8-models
+- indonesia
+- aksara
+- aksarajawa
+
+model-index:
+- name: hermanshid/yolo-aksara-jawa
+  results:
+  - task:
+      type: object-detection
+
+    metrics:
+      - type: precision  # since [email protected] is not available on hf.co/metrics
+        value: 0.995  # min: 0.0 - max: 1.0
+        name: [email protected](box)
 ---
+
+# YOLOv5 for Aksara Jawa
+
+<div align="center">
+  <img width="640" alt="hermanshid/aksarajawa" src="https://huggingface.co/hermanshid/yolo-aksara-jawa/resolve/main/thumbnail.jpg">
+</div>
+
+## Dataset
+Dataset available in [kaggle](https://www.kaggle.com/datasets/hermansugiharto/aksara-jawa-yolo-v5-dataset)
+## Supported Labels
+```python
+[
+    "ba", "ca", "da", "dha", "ga", "ha", "ja", "ka", "la", "ma",
+    "na", "nga", "nya", "pa", "ra", "sa", "ta", "tha", "wa", "ya"
+]
+```
+
+## How to use
+- Install library
+
+`pip install yolov5==7.0.5 torch`
+
+## Load model and perform prediction
+```python
+import yolov5
+from PIL import Image
+
+model = yolov5.load(models_id)
+
+model.overrides['conf'] = 0.25  # NMS confidence threshold
+model.overrides['iou'] = 0.45  # NMS IoU threshold
+model.overrides['max_det'] = 1000  # maximum number of detections per image
+
+# set image
+image = 'https://huggingface.co/spaces/hermanshid/aksara-jawa-space/raw/main/test_images/example1.jpg'
+
+# perform inference
+results = model.predict(image)
+
+# observe results
+print(results[0].boxes)
+render = render_result(model=model, image=image, result=results[0])
+render.show()
+
+```
+

config.json

@@ -1,8 +1,4 @@
 {
     "input_size": 640,
-    "task": "object-detection",
-    "ultralyticsplus_version": "0.0.28",
-    "ultralytics_version": "8.0.43",
-    "model_type": "v8",
-    "score_map50": 0.61355
+    "task": "object-detection"
 }

preprocessor_config.json

@@ -14,5 +14,5 @@
         0.225
     ],
     "max_size": 1333,
-    "size": 512
+    "size": 640
 }