diff --git a/scripts/api.py b/scripts/api.py
index 0d602db..f02d633 100644
--- a/scripts/api.py
+++ b/scripts/api.py
@@ -63,7 +63,7 @@ class SamPredictRequest(BaseModel):
     async def api_sam_predict(payload: SamPredictRequest = Body(...)) -> Any:
         print(f"SAM API /sam/sam-predict received request")
         payload.input_image = decode_to_pil(payload.input_image).convert('RGBA')
-        sam_output_mask_gallery, sam_message = sam_predict(
+        sam_output_mask_gallery, sam_message, boxes_filt = sam_predict(
             payload.sam_model_name,
             payload.input_image,
             payload.sam_positive_points,
@@ -82,6 +82,7 @@ async def api_sam_predict(payload: SamPredictRequest = Body(...)) -> Any:
             result["blended_images"] = list(map(encode_to_base64, sam_output_mask_gallery[:3]))
             result["masks"] = list(map(encode_to_base64, sam_output_mask_gallery[3:6]))
             result["masked_images"] = list(map(encode_to_base64, sam_output_mask_gallery[6:]))
+            result["boxes"] = boxes_filt.int().tolist()
         return result
 
     class DINOPredictRequest(BaseModel):
@@ -94,7 +95,7 @@ class DINOPredictRequest(BaseModel):
     async def api_dino_predict(payload: DINOPredictRequest = Body(...)) -> Any:
         print(f"SAM API /sam/dino-predict received request")
         payload.input_image = decode_to_pil(payload.input_image)
-        dino_output_img, _, dino_msg = dino_predict(
+        dino_output_img, _, dino_msg, boxes_filt = dino_predict(
             payload.input_image,
             payload.dino_model_name,
             payload.text_prompt,
@@ -107,6 +108,7 @@ async def api_dino_predict(payload: DINOPredictRequest = Body(...)) -> Any:
         return {
             "msg": dino_msg,
             "image_with_box": encode_to_base64(dino_output_img) if dino_output_img is not None else None,
+            "boxes": boxes_filt.int().tolist() if boxes_filt is not None else None
         }
 
     class DilateMaskRequest(BaseModel):
diff --git a/scripts/sam.py b/scripts/sam.py
index 775bff2..310e748 100644
--- a/scripts/sam.py
+++ b/scripts/sam.py
@@ -235,7 +235,7 @@ def sam_predict(sam_model_name, input_image, positive_points, negative_points,
             multimask_output=True)
         masks = masks[:, None, ...]
     garbage_collect(sam)
-    return create_mask_output(image_np, masks, boxes_filt), sam_predict_status + sam_predict_result + (f" However, GroundingDINO installment has failed. Your process automatically fall back to local groundingdino. Check your terminal for more detail and {dino_install_issue_text}." if (dino_enabled and not install_success) else "")
+    return create_mask_output(image_np, masks, boxes_filt), sam_predict_status + sam_predict_result + (f" However, GroundingDINO installment has failed. Your process automatically fall back to local groundingdino. Check your terminal for more detail and {dino_install_issue_text}." if (dino_enabled and not install_success) else ""), boxes_filt
 
 
 def dino_predict(input_image, dino_model_name, text_prompt, box_threshold):
@@ -245,9 +245,9 @@ def dino_predict(input_image, dino_model_name, text_prompt, box_threshold):
         return None, gr.update(), gr.update(visible=True, value=f"GroundingDINO requires text prompt.")
     image_np = np.array(input_image)
     boxes_filt, install_success = dino_predict_internal(input_image, dino_model_name, text_prompt, box_threshold)
-    boxes_filt = boxes_filt.numpy()
-    boxes_choice = [str(i) for i in range(boxes_filt.shape[0])]
-    return Image.fromarray(show_boxes(image_np, boxes_filt.astype(int), show_index=True)), gr.update(choices=boxes_choice, value=boxes_choice), gr.update(visible=False) if install_success else gr.update(visible=True, value=f"GroundingDINO installment failed. Your process automatically fall back to local groundingdino. See your terminal for more detail and {dino_install_issue_text}")
+    boxes_filt_numpy = boxes_filt.numpy()
+    boxes_choice = [str(i) for i in range(boxes_filt_numpy.shape[0])]
+    return Image.fromarray(show_boxes(image_np, boxes_filt_numpy.astype(int), show_index=True)), gr.update(choices=boxes_choice, value=boxes_choice), gr.update(visible=False) if install_success else gr.update(visible=True, value=f"GroundingDINO installment failed. Your process automatically fall back to local groundingdino. See your terminal for more detail and {dino_install_issue_text}"), boxes_filt
 
 
 def dino_batch_process(