Update export model for face detection (#501)

* support face detection in python inference

* support face detection in python deploy

deploy/python/infer.py

@@ -268,7 +268,7 @@ class Config():
     Args:
         model_dir (str): root path of model.yml
     """
-    support_models = ['YOLO', 'SSD', 'RetinaNet', 'RCNN']
+    support_models = ['YOLO', 'SSD', 'RetinaNet', 'RCNN', 'Face']
 
     def __init__(self, model_dir):
         # parsing Yaml config for Preprocess
@@ -297,8 +297,8 @@ class Config():
             if support_model in yml_conf['arch']:
                 return True
         raise ValueError(
-            "Unsupported arch: {}, expect SSD, YOLO, RetinaNet and RCNN".format(
-                yml_conf['arch']))
+            "Unsupported arch: {}, expect SSD, YOLO, RetinaNet, RCNN and Face".
+            format(yml_conf['arch']))
 
 
 def load_predictor(model_dir,
@@ -426,7 +426,7 @@ class Detector():
     def postprocess(self, np_boxes, np_masks, im_info, threshold=0.5):
         # postprocess output of predictor
         results = {}
-        if 'SSD' in self.config.arch:
+        if self.config.arch in ['SSD', 'Face']:
             w, h = im_info['origin_shape']
             np_boxes[:, 2] *= h
             np_boxes[:, 3] *= w

tools/cpp_infer.py

@@ -75,7 +75,7 @@ def get_extra_info(im, arch, shape, scale):
         im_size = np.array([shape[:2]]).astype('int32')
         logger.info('Extra info: im_size')
         info.append(im_size)
-    elif 'SSD' in arch:
+    elif arch in ['SSD', 'Face']:
         im_shape = np.array([shape[:2]]).astype('int32')
         logger.info('Extra info: im_shape')
         info.append([im_shape])
@@ -94,8 +94,8 @@ def get_extra_info(im, arch, shape, scale):
         info.append(im_shape)
     else:
         logger.error(
-            "Unsupported arch: {}, expect YOLO, SSD, RetinaNet and RCNN".format(
-                arch))
+            "Unsupported arch: {}, expect YOLO, SSD, RetinaNet, RCNN and Face".
+            format(arch))
     return info
 
 
@@ -244,6 +244,14 @@ def get_category_info(with_background, label_list):
     return clsid2catid, catid2name
 
 
+def clip_bbox(bbox):
+    xmin = max(min(bbox[0], 1.), 0.)
+    ymin = max(min(bbox[1], 1.), 0.)
+    xmax = max(min(bbox[2], 1.), 0.)
+    ymax = max(min(bbox[3], 1.), 0.)
+    return xmin, ymin, xmax, ymax
+
+
 def bbox2out(results, clsid2catid, is_bbox_normalized=False):
     """
     Args:
@@ -457,7 +465,7 @@ def draw_mask(image, masks, threshold, color_list, alpha=0.7):
 
 
 def get_bbox_result(output, result, conf, clsid2catid):
-    is_bbox_normalized = True if 'SSD' in conf['arch'] else False
+    is_bbox_normalized = True if conf['arch'] in ['SSD', 'Face'] else False
     lengths = offset_to_lengths(output.lod())
     np_data = np.array(output) if conf[
         'use_python_inference'] else output.copy_to_cpu()
@@ -513,7 +521,7 @@ def infer():
             "Due to the limitation of tensorRT, the image shape needs to set in export_model"
         )
     img_data = Preprocess(FLAGS.infer_img, conf['arch'], conf['Preprocess'])
-    if 'SSD' in conf['arch']:
+    if conf['arch'] in ['SSD', 'Face']:
         img_data, res['im_shape'] = img_data
         img_data = [img_data]
 

tools/export_model.py

@@ -47,6 +47,12 @@ def parse_reader(reader_cfg, metric, arch):
         from ppdet.utils.coco_eval import get_category_info
     if metric == "VOC":
         from ppdet.utils.voc_eval import get_category_info
+    if metric == "WIDERFACE":
+        from ppdet.utils.widerface_eval_utils import get_category_info
+    else:
+        raise ValueError(
+            "metric only supports COCO, VOC, WIDERFACE, but received {}".format(
+                metric))
     clsid2catid, catid2name = get_category_info(anno_file, with_background,
                                                 use_default_label)
     label_list = [str(cat) for cat in catid2name.values()]
@@ -90,7 +96,13 @@ def dump_infer_config(config):
         'draw_threshold': 0.5,
         'metric': config['metric']
     })
-    trt_min_subgraph = {'YOLO': 3, 'SSD': 40, 'RCNN': 40, 'RetinaNet': 40}
+    trt_min_subgraph = {
+        'YOLO': 3,
+        'SSD': 3,
+        'RCNN': 40,
+        'RetinaNet': 40,
+        'Face': 3,
+    }
     infer_arch = config['architecture']
 
     for arch, min_subgraph_size in trt_min_subgraph.items():