fix solov2 deploy (#3200)

deploy/python/infer.py

@@ -242,17 +242,20 @@ class DetectorSOLOv2(Detector):
         for i in range(warmup):
             self.predictor.run()
             output_names = self.predictor.get_output_names()
+            np_boxes_num = self.predictor.get_output_handle(output_names[
+                0]).copy_to_cpu()
             np_label = self.predictor.get_output_handle(output_names[
                 1]).copy_to_cpu()
             np_score = self.predictor.get_output_handle(output_names[
                 2]).copy_to_cpu()
             np_segms = self.predictor.get_output_handle(output_names[
                 3]).copy_to_cpu()
-
         self.det_times.inference_time_s.start()
         for i in range(repeats):
             self.predictor.run()
             output_names = self.predictor.get_output_names()
+            np_boxes_num = self.predictor.get_output_handle(output_names[
+                0]).copy_to_cpu()
             np_label = self.predictor.get_output_handle(output_names[
                 1]).copy_to_cpu()
             np_score = self.predictor.get_output_handle(output_names[
@@ -262,7 +265,11 @@ class DetectorSOLOv2(Detector):
         self.det_times.inference_time_s.end(repeats=repeats)
         self.det_times.img_num += 1
 
-        return dict(segm=np_segms, label=np_label, score=np_score)
+        return dict(
+            segm=np_segms,
+            label=np_label,
+            score=np_score,
+            boxes_num=np_boxes_num)
 
 
 def create_inputs(imgs, im_info):
@@ -481,6 +488,13 @@ def visualize(image_list, results, labels, output_dir='output/', threshold=0.5):
         if 'segm' in results:
             im_results['segm'] = results['segm'][start_idx:start_idx +
                                                  im_bboxes_num, :]
+        if 'label' in results:
+            im_results['label'] = results['label'][start_idx:start_idx +
+                                                   im_bboxes_num]
+        if 'score' in results:
+            im_results['score'] = results['score'][start_idx:start_idx +
+                                                   im_bboxes_num]
+
         start_idx += im_bboxes_num
         im = visualize_box_mask(
             image_file, im_results, labels, threshold=threshold)