Merge branch 'master' of http://git.wanmeizhensuo.com/ai/AgeGenderDist

.gitignore

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AgeGenderDist.egg-info/PKG-INFO

-Metadata-Version: 1.1
-Name: AgeGenderDist
-Version: 0.1.0
-Summary: A short description of the project
-Home-page: https://github.com/rentingting/AgeGenderDist
-Author: rentingting
-Author-email: Your address email (eq. you@example.com)
-License: BSD
-Download-URL: https://github.com/rentingting/AgeGenderDist/tarball/0.1.0
-Description: AgeGenderDist
-        ===============================
-        
-        version number: 0.1.0
-        author: rentingting
-        
-        Overview
-        --------
-        
-        A short description of the project
-        
-        Installation / Usage
-        --------------------
-        
-        To install use pip:
-        
-            $ pip install AgeGenderDist
-        
-        
-        Or clone the repo:
-        
-            $ git clone https://github.com/rentingting/AgeGenderDist.git
-            $ python setup.py install
-        
-        Contributing
-        ------------
-        
-        TBD
-        
-        Example
-        -------
-        
-        TBD
-Platform: UNKNOWN
-Classifier: Development Status :: 3 - Alpha
-Classifier: Intended Audience :: Developers
-Classifier: Programming Language :: Python :: 3

AgeGenderDist.egg-info/SOURCES.txt

-MANIFEST.in
-README.md
-requirements.txt
-setup.cfg
-setup.py
-AgeGenderDist/__init__.py
-AgeGenderDist/face_image.py
-AgeGenderDist/face_model.py
-AgeGenderDist/face_preprocess.py
-AgeGenderDist/gender.py
-AgeGenderDist/helper.py
-AgeGenderDist/mtcnn_detector.py
-AgeGenderDist/noise_sgd.py
-AgeGenderDist.egg-info/PKG-INFO
-AgeGenderDist.egg-info/SOURCES.txt
-AgeGenderDist.egg-info/dependency_links.txt
-AgeGenderDist.egg-info/requires.txt
-AgeGenderDist.egg-info/top_level.txt
-AgeGenderDist/model/model-0000.params
-AgeGenderDist/model/model-symbol.json
-AgeGenderDist/mtcnn-model/det1-0001.params
-AgeGenderDist/mtcnn-model/det1-symbol.json
-AgeGenderDist/mtcnn-model/det1.caffemodel
-AgeGenderDist/mtcnn-model/det1.prototxt
-AgeGenderDist/mtcnn-model/det2-0001.params
-AgeGenderDist/mtcnn-model/det2-symbol.json
-AgeGenderDist/mtcnn-model/det2.caffemodel
-AgeGenderDist/mtcnn-model/det2.prototxt
-AgeGenderDist/mtcnn-model/det3-0001.params
-AgeGenderDist/mtcnn-model/det3-symbol.json
-AgeGenderDist/mtcnn-model/det3.caffemodel
-AgeGenderDist/mtcnn-model/det3.prototxt
-AgeGenderDist/mtcnn-model/det4-0001.params
-AgeGenderDist/mtcnn-model/det4-symbol.json
-AgeGenderDist/mtcnn-model/det4.caffemodel
-AgeGenderDist/mtcnn-model/det4.prototxt
\ No newline at end of file

AgeGenderDist.egg-info/dependency_links.txt

-

AgeGenderDist.egg-info/requires.txt

-mxnet-cu100==1.4.1
-scipy==1.2.2
-scikit-learn==0.20.3
-opencv-python==4.1.0.25
-easydict==1.9
-scikit-image==0.14.3

AgeGenderDist.egg-info/top_level.txt

-AgeGenderDist

AgeGenderDist/face_model.py

 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-
+import math
 from scipy import misc
 import sys
 import os
 import argparse
-#import tensorflow as tf
 import numpy as np
 import mxnet as mx
 import random
@@ -18,8 +17,12 @@ from easydict import EasyDict as edict
 
 from AgeGenderDist.mtcnn_detector import MtcnnDetector
 sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src', 'common'))
-import AgeGenderDist.face_image
-import AgeGenderDist.face_preprocess
+from AgeGenderDist import face_image
+from AgeGenderDist import face_preprocess
+from pkg_resources import resource_filename
+
+
+MODEL_STR = resource_filename(__name__, "model/model")
 
 
 
@@ -27,21 +30,27 @@ def do_flip(data):
   for idx in range(data.shape[0]):
     data[idx,:,:] = np.fliplr(data[idx,:,:])
 
-def get_model(ctx, image_size, model_str, layer):
-  _vec = model_str.split(',')
-  assert len(_vec)==2
-  prefix = _vec[0]
-  epoch = int(_vec[1])
-  print('loading',prefix, epoch)
+def get_model(ctx, image_size, layer):
+  epoch = 0
+  prefix = MODEL_STR
   sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
   all_layers = sym.get_internals()
   sym = all_layers[layer+'_output']
   model = mx.mod.Module(symbol=sym, context=ctx, label_names = None)
-  #model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0], image_size[1]))], label_shapes=[('softmax_label', (args.batch_size,))])
   model.bind(data_shapes=[('data', (1, 3, image_size[0], image_size[1]))])
   model.set_params(arg_params, aux_params)
   return model
 
+
+class FaceModelArgs:
+  def __init__(self, image_size='112,112', gpu=0, det=0, flip=0, threshold=1.24):
+    self.image_size = image_size
+    self.gpu = gpu
+    self.det = det
+    self.flip = flip
+    self.threshold = threshold
+
+
 class FaceModel:
   def __init__(self, args):
     self.args = args
@@ -53,8 +62,7 @@ class FaceModel:
     assert len(_vec)==2
     image_size = (int(_vec[0]), int(_vec[1]))
     self.model = None
-    if len(args.model)>0:
-      self.model = get_model(ctx, image_size, args.model, 'fc1')
+    self.model = get_model(ctx, image_size, 'fc1')
 
     self.det_minsize = 50
     self.det_threshold = [0.6,0.7,0.8]
@@ -70,7 +78,6 @@ class FaceModel:
 
   def get_input(self, face_img):
     ret = self.detector.detect_face(face_img, det_type = self.args.det)
-    #print('ret',ret)
     if ret is None:
       return None
     bbox, points = ret
@@ -78,16 +85,13 @@ class FaceModel:
       return None
     bbox = bbox[0,0:4]
     points = points[0,:].reshape((2,5)).T
-    #print(bbox)
-    #print(points)
     nimg = face_preprocess.preprocess(face_img, bbox, points, image_size='112,112')
     nimg = cv2.cvtColor(nimg, cv2.COLOR_BGR2RGB)
     aligned = np.transpose(nimg, (2,0,1))
     input_blob = np.expand_dims(aligned, axis=0)
     data = mx.nd.array(input_blob)
     db = mx.io.DataBatch(data=(data,))
-    return db
-
+    return db, ret
 
   def get_ga(self, data):
     self.model.forward(data, is_train=False)
@@ -100,3 +104,18 @@ class FaceModel:
 
     return gender, age
 
+  def get_age_gender_dist(self, img_src):
+    img, ret =self.get_input(img_src)
+    if ret is None:
+        print('ret is none')
+        return None
+    bbox, points = ret
+    points = points[0,:].reshape((2,5)).T
+    im=img_src.copy()
+    lf_eye=points[0]
+    rt_eye=points[1]
+    tmp=rt_eye-lf_eye
+    dist=math.hypot(tmp[0],tmp[1])
+    gender,age=self.get_ga(img)
+    return age,gender,dist
+

AgeGenderDist/gender.py

-import AgeGenderDist.face_model
+from AgeGenderDist import face_model
 import argparse
 import cv2
 import sys
@@ -41,11 +41,11 @@ def get_age_gender_dist(img_src):
    rt_eye=points[1]
    tmp=rt_eye-lf_eye
    dist=math.hypot(tmp[0],tmp[1])
-  
+
    model=face_model.FaceModel(args)
    img=model.get_input(img_src)
    gender,age=model.get_ga(img)
-    
+
    return age,gender,dist
 
 def get_gender_age(img):
@@ -54,7 +54,7 @@ def get_gender_age(img):
     gender,age=model.get_ga(img)
     return gender,age
 
-if __name__=='__main__':          
+if __name__=='__main__':
    dirs= os.listdir(args.image)
    for file in dirs:
        print('file',file)

AgeGenderDist/mtcnn_detector.py

@@ -6,9 +6,11 @@ import math
 import cv2
 from multiprocessing import Pool
 from itertools import repeat
-#from itertools import zip_longest as zip
-from itertools import izip
-from helper import nms, adjust_input, generate_bbox, detect_first_stage_warpper
+try:
+    from itertools import izip
+except ImportError:
+    izip = zip
+from AgeGenderDist.helper import nms, adjust_input, generate_bbox, detect_first_stage_warpper
 
 class MtcnnDetector(object):
     """
@@ -49,7 +51,7 @@ class MtcnnDetector(object):
         # load 4 models from folder
         models = ['det1', 'det2', 'det3','det4']
         models = [ os.path.join(model_folder, f) for f in models]
-        
+
         self.PNets = []
         for i in range(num_worker):
             workner_net = mx.model.FeedForward.load(models[0], 1, ctx=ctx)
@@ -115,7 +117,7 @@ class MtcnnDetector(object):
         bbox[:, 0:4] = bbox[:, 0:4] + aug
         return bbox
 
- 
+
     def pad(self, bboxes, w, h):
         """
             pad the the bboxes, alse restrict the size of it
@@ -185,7 +187,7 @@ class MtcnnDetector(object):
                 yield l[i:i + n]
         num_list = range(number)
         return list(chunks(num_list, self.num_worker))
-        
+
     def detect_face_limited(self, img, det_type=2):
         height, width, _ = img.shape
         if det_type>=2:
@@ -257,7 +259,7 @@ class MtcnnDetector(object):
         pick = nms(total_boxes, 0.7, 'Min')
         total_boxes = total_boxes[pick]
         points = points[pick]
-        
+
         if not self.accurate_landmark:
             return total_boxes, points
 
@@ -350,7 +352,7 @@ class MtcnnDetector(object):
             #    return_boxes = self.detect_first_stage(img, scale, 0)
             #    if return_boxes is not None:
             #        total_boxes.append(return_boxes)
-            
+
             sliced_index = self.slice_index(len(scales))
             total_boxes = []
             for batch in sliced_index:
@@ -359,14 +361,14 @@ class MtcnnDetector(object):
                 local_boxes = map( detect_first_stage_warpper, \
                         izip(repeat(img), self.PNets[:len(batch)], [scales[i] for i in batch], repeat(self.threshold[0])) )
                 total_boxes.extend(local_boxes)
-            
+
                 #print('local_boxes',local_boxes)
-            # remove the Nones 
+            # remove the Nones
             total_boxes = [ i for i in total_boxes if i is not None]
 
             if len(total_boxes) == 0:
                 return None
-            
+
             total_boxes = np.vstack(total_boxes)
 
             if total_boxes.size == 0:
@@ -466,7 +468,7 @@ class MtcnnDetector(object):
         pick = nms(total_boxes, 0.7, 'Min')
         total_boxes = total_boxes[pick]
         points = points[pick]
-        
+
         if not self.accurate_landmark:
             return total_boxes, points
 
@@ -521,7 +523,7 @@ class MtcnnDetector(object):
                 input list
         Retures:
         -------
-            colMat: 
+            colMat:
 
         """
         assert len(pts_list) > 0
@@ -537,8 +539,8 @@ class MtcnnDetector(object):
             find transform between shapes
         Parameters:
         ----------
-            from_shape: 
-            to_shape: 
+            from_shape:
+            to_shape:
         Retures:
         -------
             tran_m:
@@ -599,7 +601,7 @@ class MtcnnDetector(object):
         Retures:
         -------
             crop_imgs: list, n
-                cropped and aligned faces 
+                cropped and aligned faces
         """
         crop_imgs = []
         for p in points:

README.md

-AgeGenderDist
-===============================
+# AgeGenderDist
 
-version number: 0.1.0
-author: rentingting
+人脸尺寸测量库
 
-Overview
---------
+## 安装
 
-A short description of the project
+1. pip 安装
 
-Installation / Usage
---------------------
+```shell
+pip install git@git.wanmeizhensuo.com:ai/AgeGenderDist.git#egg=AgeGenderDist
+```
 
-To install use pip:
+## 使用方式
 
-    $ pip install AgeGenderDist
+```python
+from AgeGenderDist.face_model import FaceModel, FaceModelArgs
+import cv2
+args = FaceModelArgs()
+model = FaceModel(args)
 
-
-Or clone the repo:
-
-    $ git clone https://github.com/rentingting/AgeGenderDist.git
-    $ python setup.py install
-
-Contributing
-------------
-
-TBD
-
-Example
--------
-
-TBD
\ No newline at end of file
+img = cv2.imread('./lihaonan.jpg')
+age, gender, dist = model.get_age_gender_dist(img)
+print(age)  # 年龄
+print(gender)  # 性别 0: 女 1: 男
+print(dist)  # 瞳距 单位 px
+```

requirements.txt

 # Dev/Deployment
-mxnet-cu100==1.4.1
+mxnet
 scipy==1.2.2
 scikit-learn==0.20.3
 opencv-python==4.1.0.25