Update app.py

app.py

@@ -25,12 +25,12 @@ model = AutoDetectionModel.from_pretrained(
 def sahi_yolo_inference(
     model_type,
     image,
-    slice_height=512,
-    slice_width=512,
-    overlap_height_ratio=0.2,
-    overlap_width_ratio=0.2,
-    postprocess_type="GREEDYNMM",
-    postprocess_match_metric="IOS",
+    slice_height=1280,
+    slice_width=1280,
+    overlap_height_ratio=0.1,
+    overlap_width_ratio=0.1,
+    postprocess_type="NMS",
+    postprocess_match_metric="IOU",
     postprocess_match_threshold=0.5,
     postprocess_class_agnostic=False,
 ):
@@ -99,18 +99,18 @@ def sahi_yolo_inference(
 inputs = [
     gr.inputs.Dropdown(choices=model_types,label="Choose Model Type",type="value",),
     gr.inputs.Image(type="pil", label="Original Image"),
-    gr.inputs.Number(default=512, label="slice_height"),
-    gr.inputs.Number(default=512, label="slice_width"),
-    gr.inputs.Number(default=0.2, label="overlap_height_ratio"),
-    gr.inputs.Number(default=0.2, label="overlap_width_ratio"),
+    gr.inputs.Number(default=1920 label="slice_height"),
+    gr.inputs.Number(default=1920, label="slice_width"),
+    gr.inputs.Number(default=0.1, label="overlap_height_ratio"),
+    gr.inputs.Number(default=0.1, label="overlap_width_ratio"),
     gr.inputs.Dropdown(
         ["NMS", "GREEDYNMM"],
         type="value",
-        default="GREEDYNMM",
+        default="NMS",
         label="postprocess_type",
     ),
     gr.inputs.Dropdown(
-        ["IOU", "IOS"], type="value", default="IOS", label="postprocess_type"
+        ["IOU", "IOS"], type="value", default="IOU", label="postprocess_type"
     ),
     gr.inputs.Number(default=0.5, label="postprocess_match_threshold"),
     gr.inputs.Checkbox(default=True, label="postprocess_class_agnostic"),
@@ -124,10 +124,10 @@ title = "Small Object Detection with SAHI + YOLOv5"
 description = "SAHI + YOLOv5 demo for small object detection. Upload an image or click an example image to use."
 article = "<p style='text-align: center'>SAHI is a lightweight vision library for performing large scale object detection/ instance segmentation.. <a href='https://github.com/obss/sahi'>SAHI Github</a> | <a href='https://medium.com/codable/sahi-a-vision-library-for-performing-sliced-inference-on-large-images-small-objects-c8b086af3b80'>SAHI Blog</a> | <a href='https://github.com/fcakyon/yolov5-pip'>YOLOv5 Github</a> </p>"
 examples = [
-    [model_types[0],"26.jpg", 256, 256, 0.2, 0.2, "GREEDYNMM", "IOS", 0.5, True],
-    [model_types[0],"27.jpg", 512, 512, 0.2, 0.2, "GREEDYNMM", "IOS", 0.5, True],
-    [model_types[0],"28.jpg", 512, 512, 0.2, 0.2, "GREEDYNMM", "IOS", 0.5, True],
-    [model_types[0],"31.jpg", 512, 512, 0.2, 0.2, "GREEDYNMM", "IOS", 0.5, True],
+    [model_types[0],"26.jpg", 256, 256, 0.2, 0.2, "NMS", "IOU", 0.5, True],
+    [model_types[0],"27.jpg", 512, 512, 0.2, 0.2, "NMS", "IOU", 0.5, True],
+    [model_types[0],"28.jpg", 512, 512, 0.2, 0.2, "NMS", "IOU", 0.5, True],
+    [model_types[0],"31.jpg", 512, 512, 0.2, 0.2, "NMS", "IOU", 0.5, True],
 
 ]
 gr.Interface(