fix title

.gitattributes

@@ -33,3 +33,8 @@ 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
+test_images/ filter=lfs diff=lfs merge=lfs -text
+test_images/example2.jpg filter=lfs diff=lfs merge=lfs -text
+test_images/example3.jpg filter=lfs diff=lfs merge=lfs -text
+test_images/example1.jpg filter=lfs diff=lfs merge=lfs -text
+install filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,7 +1,7 @@
 ---
 title: Aksara Jawa Space
 emoji: ⚡
-colorFrom: pink
+colorFrom: blue
 colorTo: green
 sdk: gradio
 sdk_version: 3.44.4

app.py

@@ -4,20 +4,16 @@ import yolov5
 from PIL import Image
 
 app_title = "Aksara Jawa Object Detection"
-models_ids = ['hermanshid/yolo-aksara-jawa']
+models_id = 'hermanshid/yolo-aksara-jawa'
 
-current_model_id = models_ids[-1]
-model = yolov5.load(current_model_id)
+model = yolov5.load(models_id)
 
-examples = [['test_images/hanacaraka.jpg', 0.25, 'hermanshid/yolo-aksara-jawa']]
+examples = [['test_images/example1.jpg', 0.9, ]]
 
 
-def predict(image, threshold=0.25, model_id=None):
-    global current_model_id
+def predict(image, threshold=0.25):
+    global models_id
     global model
-    if model_id != current_model_id:
-        model = yolov5.load(model_id)
-        current_model_id = model_id
 
     input_size = 640
 
@@ -35,7 +31,6 @@ gr.Interface(
     inputs=[
         gr.Image(type="pil"),
         gr.Slider(maximum=1, step=0.01, value=0.25),
-        gr.Dropdown(models_ids, value=models_ids[-1]),
     ],
     outputs=gr.Image(type="pil"),
     examples=examples,