feat: add json output

.gitignore

@@ -2,4 +2,5 @@
 yolov5s.pt
 # __pycache__
 *.jpg
-gradio_queue.db
+gradio_queue.db
+__pycache__

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import torch
 from PIL import Image
+import json
 
 # Images
 torch.hub.download_url_to_file(
@@ -22,11 +23,21 @@ def yolo(im, size=1024):
 
     results = model(im)  # inference
     results.render()  # updates results.imgs with boxes and labels
-    return Image.fromarray(results.imgs[0])
+
+    df = results.pandas().xyxy[0].to_json(orient="records")
+    res = json.loads(df)
+
+    return [
+        Image.fromarray(results.imgs[0]),
+        res
+    ]
 
 
 inputs = gr.inputs.Image(type='pil', label="Original Image")
-outputs = gr.outputs.Image(type="pil", label="Output Image")
+outputs = [
+    gr.outputs.Image(type="pil", label="Output Image"),
+    gr.outputs.JSON(label="Output JSON")
+]
 
 title = "YOLOv5 NDL-DocL Datasets"
 description = "YOLOv5 NDL-DocL Datasets Gradio demo for object detection. Upload an image or click an example image to use."