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.gitattributes

@@ -33,3 +33,5 @@ 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
+image1.jpg filter=lfs diff=lfs merge=lfs -text
+image2.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,38 @@
+from ultralytics import YOLO
+import cv2 
+import gradio as gr
+
+file = "my_model.pt"
+images = [["image1.jpg"],["image2.jpg"]]
+model = YOLO(file)
+
+def show_preds_image(image_path):
+    image = cv2. imread(image_path)
+    outputs = model.predict(source=image_path)
+    results = outputs[0]. cpu().numpy()
+    for i, det in enumerate(results.boxes.xyxy):
+        cv2. rectangle(image,(int(det[0]), int(det[1])), (int(det[2]), int(det[3])),
+                       thickness=2 , color=[0,255,0]
+                       )
+    return cv2. cvtColor (image, cv2.COLOR_BGR2RGB)
+
+
+inputs_image = [
+    gr.components.Image(type="filepath", label="Input Image"),
+]
+outputs_image = [
+    gr.components.Image(type="numpy", label="Output Image"),
+]
+
+interface_image = gr.Interface(
+    fn=show_preds_image,
+    inputs=inputs_image,
+    outputs=outputs_image,
+    title="Plastic Detector",
+    examples=images,
+    cache_examples=False,
+)
+
+interface_image.launch()
+
+

my_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4305da01e86751f7c094615f04997e62d145a85ec16efe247f2ad4b89f25de1f
+size 19182419

requirements.txt

@@ -0,0 +1,5 @@
+ultralytics==8.3.80
+Pillow==9.4.0
+httpx==0.24.1
+gradio==3.35.2
+gradio_client==0.2.7