update face_landmark_localization (#1966)

* update face_landmark_localization

* fix typo

* update

* add clean func

* update save inference model

* update save inference model
Co-authored-by: Nchenjian <chenjian26@baidu.com>

modules/image/keypoint_detection/face_landmark_localization/README.md

@@ -120,18 +120,11 @@
       - 当前模型使用的人脸检测模型。
 
   - ```python
-    def save_inference_model(dirname,
-                             model_filename=None,
-                             params_filename=None,
-                             combined=False):
+    def save_inference_model(dirname):
     ```
-
-    - 将模型保存到指定路径，由于人脸关键点检测模型由人脸检测+关键点检测两个模型组成，因此保存后会存在两个子目录，其中`face_landmark`为人脸关键点模型，`detector`为人脸检测模型。
+    
     - **参数**
-      - dirname: 存在模型的目录名称
-      - model_filename: 模型文件名称，默认为\__model__
-      - params_filename: 参数文件名称，默认为\__params__(仅当combined为True时生效)
-      - combined: 是否将参数保存到统一的一个文件中
+      - dirname: 模型保存路径
 
 ## 四、服务部署
 
@@ -187,6 +180,10 @@
 
   移除 fluid api
 
+* 1.1.0
+
+  修复无法导出推理模型的问题
+
   * ```shell
-    $ hub install face_landmark_localization==1.0.3
+    $ hub install face_landmark_localization==1.1.0
     ```

modules/image/keypoint_detection/face_landmark_localization/data_feed.py

 # coding=utf-8
 import os
-import time
 from collections import OrderedDict
 
 import cv2
 import numpy as np
-from PIL import Image
 
 __all__ = ['reader']
 

modules/image/keypoint_detection/face_landmark_localization/module.py

@@ -5,15 +5,14 @@ from __future__ import division
 import argparse
 import ast
 import os
-import time
-from collections import OrderedDict
 
-import cv2
 import numpy as np
 import paddle
-from face_landmark_localization.data_feed import reader
-from face_landmark_localization.processor import base64_to_cv2
-from face_landmark_localization.processor import postprocess
+import paddle.jit
+import paddle.static
+from .data_feed import reader
+from .processor import base64_to_cv2
+from .processor import postprocess
 from paddle.inference import Config
 from paddle.inference import create_predictor
 
@@ -30,15 +29,14 @@ from paddlehub.module.module import serving
     author_email="paddle-dev@baidu.com",
     summary=
     "Face_Landmark_Localization can be used to locate face landmark. This Module is trained through the MPII Human Pose dataset.",
-    version="1.0.3")
-class FaceLandmarkLocalization(hub.Module):
-
-    def _initialize(self, face_detector_module=None):
+    version="1.1.0")
+class FaceLandmarkLocalization:
+    def __init__(self, face_detector_module=None):
         """
         Args:
             face_detector_module (class): module to detect face.
         """
-        self.default_pretrained_model_path = os.path.join(self.directory, "face_landmark_localization")
+        self.default_pretrained_model_path = os.path.join(self.directory, "face_landmark_localization", "model")
         if face_detector_module is None:
             self.face_detector = hub.Module(name="ultra_light_fast_generic_face_detector_1mb_640")
         else:
@@ -49,7 +47,9 @@ class FaceLandmarkLocalization(hub.Module):
         """
         predictor config setting
         """
-        cpu_config = Config(self.default_pretrained_model_path)
+        model = self.default_pretrained_model_path+'.pdmodel'
+        params = self.default_pretrained_model_path+'.pdiparams'
+        cpu_config = Config(model, params)
         cpu_config.disable_glog_info()
         cpu_config.disable_gpu()
         self.cpu_predictor = create_predictor(cpu_config)
@@ -61,7 +61,7 @@ class FaceLandmarkLocalization(hub.Module):
         except:
             use_gpu = False
         if use_gpu:
-            gpu_config = Config(self.default_pretrained_model_path)
+            gpu_config = Config(model, params)
             gpu_config.disable_glog_info()
             gpu_config.enable_use_gpu(memory_pool_init_size_mb=1000, device_id=0)
             self.gpu_predictor = create_predictor(gpu_config)
@@ -78,30 +78,6 @@ class FaceLandmarkLocalization(hub.Module):
     def get_face_detector_module(self):
         return self.face_detector
 
-    def save_inference_model(self, dirname, model_filename=None, params_filename=None, combined=True):
-        if combined:
-            model_filename = "__model__" if not model_filename else model_filename
-            params_filename = "__params__" if not params_filename else params_filename
-        place = paddle.CPUPlace()
-        exe = paddle.Executor(place)
-
-        program, feeded_var_names, target_vars = paddle.static.load_inference_model(
-            dirname=self.default_pretrained_model_path, executor=exe)
-        face_landmark_dir = os.path.join(dirname, "face_landmark")
-        detector_dir = os.path.join(dirname, "detector")
-
-        paddle.static.save_inference_model(dirname=face_landmark_dir,
-                                           main_program=program,
-                                           executor=exe,
-                                           feeded_var_names=feeded_var_names,
-                                           target_vars=target_vars,
-                                           model_filename=model_filename,
-                                           params_filename=params_filename)
-        self.face_detector.save_inference_model(dirname=detector_dir,
-                                                model_filename=model_filename,
-                                                params_filename=params_filename,
-                                                combined=combined)
-
     def keypoint_detection(self,
                            images=None,
                            paths=None,

modules/image/keypoint_detection/face_landmark_localization/processor.py

@@ -6,7 +6,6 @@ from __future__ import print_function
 import base64
 import os
 import time
-from collections import OrderedDict
 
 import cv2
 import numpy as np

modules/image/keypoint_detection/face_landmark_localization/test.py

+import os
+import shutil
+import unittest
+
+import cv2
+import requests
+import paddlehub as hub
+
+
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
+
+class TestHubModule(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls) -> None:
+        img_url = 'https://ai-studio-static-online.cdn.bcebos.com/7799a8ccc5f6471b9d56fb6eff94f82a08b70ca2c7594d3f99877e366c0a2619'
+        if not os.path.exists('tests'):
+            os.makedirs('tests')
+        response = requests.get(img_url)
+        assert response.status_code == 200, 'Network Error.'
+        with open('tests/test.jpg', 'wb') as f:
+            f.write(response.content)
+        cls.module = hub.Module(name="face_landmark_localization")
+
+    @classmethod
+    def tearDownClass(cls) -> None:
+        shutil.rmtree('tests')
+        shutil.rmtree('inference')
+        shutil.rmtree('face_landmark_output')
+
+    def test_keypoint_detection1(self):
+        results = self.module.keypoint_detection(
+            paths=['tests/test.jpg'],
+            use_gpu=False,
+            visualization=False
+        )
+        kps = results[0]['data'][0]
+        self.assertIsInstance(kps, list)
+
+    def test_keypoint_detection2(self):
+        results = self.module.keypoint_detection(
+            images=[cv2.imread('tests/test.jpg')],
+            use_gpu=False,
+            visualization=False
+        )
+        kps = results[0]['data'][0]
+        self.assertIsInstance(kps, list)
+
+    def test_keypoint_detection3(self):
+        results = self.module.keypoint_detection(
+            images=[cv2.imread('tests/test.jpg')],
+            use_gpu=False,
+            visualization=True
+        )
+        kps = results[0]['data'][0]
+        self.assertIsInstance(kps, list)
+
+    def test_keypoint_detection4(self):
+        results = self.module.keypoint_detection(
+            images=[cv2.imread('tests/test.jpg')],
+            use_gpu=True,
+            visualization=False
+        )
+        kps = results[0]['data'][0]
+        self.assertIsInstance(kps, list)
+
+    def test_keypoint_detection5(self):
+        self.assertRaises(
+            AssertionError,
+            self.module.keypoint_detection,
+            paths=['no.jpg']
+        )
+
+    def test_keypoint_detection6(self):
+        self.assertRaises(
+            AttributeError,
+            self.module.keypoint_detection,
+            images=['test.jpg']
+        )
+
+    def test_save_inference_model(self):
+        self.module.save_inference_model('./inference/model')
+
+        self.assertTrue(os.path.exists('./inference/model/model.pdmodel'))
+        self.assertTrue(os.path.exists('./inference/model/model.pdiparams'))
+
+        self.assertTrue(os.path.exists('./inference/model/face_detector.pdmodel'))
+        self.assertTrue(os.path.exists('./inference/model/face_detector.pdiparams'))
+
+if __name__ == "__main__":
+    unittest.main()