Update app.py

app.py

@@ -25,10 +25,11 @@ fdic = {
     "weight" : "bold"
 }
 
+
 def get_figure(in_pil_img, in_results):
-    plt.figure(figsize=(16,10))
+    plt.figure(figsize=(16, 10))
     plt.imshow(in_pil_img)
-
+    #pyplot.gcf()
     ax = plt.gca()
 
     for prediction in in_results:
@@ -36,13 +37,17 @@ def get_figure(in_pil_img, in_results):
 
         x, y = prediction['box']['xmin'], prediction['box']['ymin'],
         w, h = prediction['box']['xmax'] - prediction['box']['xmin'], prediction['box']['ymax'] - prediction['box']['ymin']
+
         ax.add_patch(plt.Rectangle((x, y), w, h, fill=False, color=selected_color, linewidth=3))
         ax.text(x, y, f"{prediction['label']}: {round(prediction['score']*100, 1)}%", fontdict=fdic)
 
     plt.axis("off")
+
     return plt.gcf()
-    
+
+
 def infer(model, in_pil_img):
+
     results = None
     if model == "detr-resnet-101":
         results = detector101(in_pil_img)
@@ -58,6 +63,7 @@ def infer(model, in_pil_img):
 
     return output_pil_img
 
+
 with gr.Blocks(title="DETR Object Detection - ClassCat",
                     css=".gradio-container {background:lightyellow;}"
                ) as demo:
@@ -93,5 +99,4 @@ with gr.Blocks(title="DETR Object Detection - ClassCat",
 
 
 #demo.queue()
-demo.launch(debug=True)
- 
+demo.launch(debug=True)