feat: add readme

README.md

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+---
+tags:
+- ultralyticsplus
+- yolov5
+- ultralytics
+- yolo
+- vision
+- object-detection
+- pytorch
+- indonesia
+- aksara
+- aksarajawa
+
+model-index:
+- name: ariffaizin19/yolov5-sewaka-detc
+  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)
+inference: false
+---
+# YOLOv5 for Aksara Jawa
+
+<div align="center">
+  <img width="640" alt="ariffaizin19/aksarajawa" src="https://huggingface.co/ariffaizin19/yolov5-sewaka-detc/resolve/main/thumbnail.jpg">
+</div>
+
+## Supported Labels
+```python
+[
+    '1 Ha', '2 Na', '3 Ca', '4 Ra', '5 Ka', '6 Da', '7 Ta', '8 Sa', '9 Wa', '10 La', 
+    '11 Pa', '12 Dha', '13 Ja', '14 Ya', '15 Nya', '16 Ma', '17 Ga', '18 Ba', '19 Tha', '20 Nga', 
+    '21 Pasangan Ha', '22 Pasangan Na', '23 Pasangan Ca', '24 Pasangan Ra', '25 Pasangan Ka', 
+    '26 Pasangan Da', '27 Pasangan Ta', '28 Pasangan Sa', '29 Pasangan Wa', '30 Pasangan La', 
+    '31 Pasangan Pa', '32 Pasangan Dha', '33 Pasangan Ja', '34 Pasangan Ya', '35 Pasangan Nya', 
+    '36 Pasangan Ma', '37 Pasangan Ga', '38 Pasangan Ba', '39 Pasangan Tha', '40 Pasangan Nga', 
+    '41 Wulu', '42 Pepet', '43 Suku', '44 Taling', '45 Taling Tarung', 
+    '46 Cecak', '47 Layar', '48 Pangkon', '49 Pengkol', '50 Wignyan', 
+    '51 Cakra', '52 Pa Cerek', '53 Nga Lelet', '54 Pada Lingsa', '55 Pada Madya', '56 Purwa Pada', 
+    '57 Murda Na', '58 Murda Ka', '59 Murda Ta', '60 Murda Sa', '61 Murda Pa', '63 Murda Ga', '64 Murda Ba', 
+    '67 Pasangan Murda Ga', '71 Pasangan Murda Ta', 
+    '73 Rekan Kha', '76 Rekan Za', 
+    '81 Pasangan Murda Za', 
+    '83 Swara A', '84 Swara E', '85 Swara U', '86 Swara I', 
+    '95 Mahaprana Sha', '97 Cakra Keret'
+]
+```
+
+## 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/ariffaizin19/yolov5-sewaka-detc/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()
+```