code: def get_keypoint_res(results, im_id):
      anns = []
      preds = results["keypoint"]
      for idx in range(im_id.shape[0]):
          image_id = im_id[idx].item()
          kpts, scores = preds[idx]
          for kpt, score in zip(kpts, scores):
              kpt = kpt.flatten()
              ann = {
                  "image_id": image_id,
                  "category_id": 1,  # XXX hard code
                  "keypoints": kpt.tolist(),
                  "score": float(score),
              }
              x = kpt[0::3]
              y = kpt[1::3]
              x0, x1, y0, y1 = (
                  np.min(x).item(),
                  np.max(x).item(),
                  np.min(y).item(),
                  np.max(y).item(),
              )
              ann["area"] = (x1 - x0) * (y1 - y0)
              ann["bbox"] = [x0, y0, x1 - x0, y1 - y0]
              anns.append(ann)
      return anns
  
file_path: PaddleDetection/ppdet/metrics/json_results.py
imports: import six
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: get_keypoint_res(results, im_id) and returns: anns