diff --git a/deploy/__init__.py b/deploy/__init__.py
new file mode 100644
index 00000000..b7744fda
--- /dev/null
+++ b/deploy/__init__.py
@@ -0,0 +1,3 @@
+from .predict import detect
+
+__all__ = ['detect']
\ No newline at end of file
diff --git a/tests/modules/test_deploy_predict.py b/tests/modules/test_deploy_predict.py
new file mode 100644
index 00000000..7951a443
--- /dev/null
+++ b/tests/modules/test_deploy_predict.py
@@ -0,0 +1,51 @@
+import sys
+
+sys.path.append(".")
+import os
+import numpy as np
+from download import download
+import cv2
+
+from mindspore import nn
+
+from mindyolo.utils.metrics import non_max_suppression, scale_coords, xyxy2xywh
+from mindyolo.data import COCO80_TO_COCO91_CLASS
+from deploy.infer_engine.lite import LiteModel
+from mindyolo.utils.utils import draw_result
+from deploy.predict import detect
+
+def test_deploy_predict():
+    image_url = 'https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/datasets/image_cat.zip'
+    path = download(image_url, './', kind="zip", replace=True)
+    image_path = ('./image_cat/jpg/000000039769.jpg')
+
+    model_url = 'https://download.mindspore.cn/toolkits/mindyolo/yolov5/yolov5n_300e_mAP273-9b16bd7b-bd03027b.mindir'
+    model_path = download(model_url, './yolov5n.mindir', kind="file", replace=True)
+
+    network = LiteModel(model_path)
+    img = cv2.imread(image_path)
+    result_dict = detect(
+        network=network,
+        img=img,
+        conf_thres=0.1,
+        iou_thres=0.65,
+        conf_free=False,
+        nms_time_limit=20,
+        img_size=640,
+        is_coco_dataset=True,
+    )
+    save_path = os.path.join('./', "detect_results")
+    names = [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
+           'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
+           'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
+           'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
+           'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
+           'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
+           'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
+           'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
+           'hair drier', 'toothbrush' ]
+    draw_result(image_path, result_dict, names, save_path=save_path)
+
+
+if __name__ == '__main__':
+    test_deploy_predict()