From 852324d6e0b65b4f3483058c7cfce6d17424599f Mon Sep 17 00:00:00 2001
From: zhiboniu <31800336+zhiboniu@users.noreply.github.com>
Date: Wed, 3 Aug 2022 18:49:04 +0800
Subject: [PATCH] update attribute docs (#6574)

---
 deploy/pipeline/pphuman/attr_infer.py         |  7 +-
 .../customization/attribute.md                | 99 +++++++++++++++++++
 2 files changed, 102 insertions(+), 4 deletions(-)

diff --git a/deploy/pipeline/pphuman/attr_infer.py b/deploy/pipeline/pphuman/attr_infer.py
index f783d5e5c..dfbdd8f68 100644
--- a/deploy/pipeline/pphuman/attr_infer.py
+++ b/deploy/pipeline/pphuman/attr_infer.py
@@ -142,13 +142,12 @@ class AttrDetector(Detector):
             bag_label = bag if bag_score > self.threshold else 'No bag'
             label_res.append(bag_label)
             # upper
-            upper_res = res[4:8]
             upper_label = 'Upper:'
             sleeve = 'LongSleeve' if res[3] > res[2] else 'ShortSleeve'
             upper_label += ' {}'.format(sleeve)
-            for i, r in enumerate(upper_res):
-                if r > self.threshold:
-                    upper_label += ' {}'.format(upper_list[i])
+            upper_res = res[4:8]
+            if np.max(upper_res) > self.threshold:
+                upper_label += ' {}'.format(upper_list[np.argmax(upper_res)])
             label_res.append(upper_label)
             # lower
             lower_res = res[8:14]
diff --git a/docs/advanced_tutorials/customization/attribute.md b/docs/advanced_tutorials/customization/attribute.md
index b7abe48b1..833dfc322 100644
--- a/docs/advanced_tutorials/customization/attribute.md
+++ b/docs/advanced_tutorials/customization/attribute.md
@@ -192,3 +192,102 @@ ATTR:
 
 删减属性同理。
 例如，如果不需要年龄属性，则位置[19, 20, 21]的数值可以去掉。只需在train.txt中标注的26个数字中全部删除第19-21位数值即可，同时标注数据时也不再需要标注这3位属性值。
+
+## 修改后处理代码
+
+修改了属性定义后，pipeline后处理部分也需要做相应修改，主要影响结果可视化时的显示结果。
+
+相应代码在路径`deploy/pipeline/pphuman/attr_infer.py`文件中`postprocess`函数。
+
+其函数实现说明如下：
+
+```
+# 函数入口
+    def postprocess(self, inputs, result):
+        # postprocess output of predictor
+        im_results = result['output']
+
+# 1) 定义各组属性实际意义，其数量及位置与输出结果中占用位数一一对应。
+        labels = self.pred_config.labels
+        age_list = ['AgeLess18', 'Age18-60', 'AgeOver60']
+        direct_list = ['Front', 'Side', 'Back']
+        bag_list = ['HandBag', 'ShoulderBag', 'Backpack']
+        upper_list = ['UpperStride', 'UpperLogo', 'UpperPlaid', 'UpperSplice']
+        lower_list = [
+            'LowerStripe', 'LowerPattern', 'LongCoat', 'Trousers', 'Shorts',
+            'Skirt&Dress'
+        ]
+# 2） 部分属性所用阈值与通用值有明显区别，单独设置
+        glasses_threshold = 0.3
+        hold_threshold = 0.6
+
+        batch_res = []
+        for res in im_results:
+            res = res.tolist()
+            label_res = []
+            # gender
+# 3) 单个位置属性类别，判断该位置是否大于阈值，来分配二分类结果
+            gender = 'Female' if res[22] > self.threshold else 'Male'
+            label_res.append(gender)
+            # age
+# 4）多个位置属性类别，N选一形式，选择得分最高的属性
+            age = age_list[np.argmax(res[19:22])]
+            label_res.append(age)
+            # direction
+            direction = direct_list[np.argmax(res[23:])]
+            label_res.append(direction)
+            # glasses
+            glasses = 'Glasses: '
+            if res[1] > glasses_threshold:
+                glasses += 'True'
+            else:
+                glasses += 'False'
+            label_res.append(glasses)
+            # hat
+            hat = 'Hat: '
+            if res[0] > self.threshold:
+                hat += 'True'
+            else:
+                hat += 'False'
+            label_res.append(hat)
+            # hold obj
+            hold_obj = 'HoldObjectsInFront: '
+            if res[18] > hold_threshold:
+                hold_obj += 'True'
+            else:
+                hold_obj += 'False'
+            label_res.append(hold_obj)
+            # bag
+            bag = bag_list[np.argmax(res[15:18])]
+            bag_score = res[15 + np.argmax(res[15:18])]
+            bag_label = bag if bag_score > self.threshold else 'No bag'
+            label_res.append(bag_label)
+            # upper
+# 5）同一类属性，分为两组（这里是款式和花色），每小组内单独选择，相当于两组不同属性。
+            upper_label = 'Upper:'
+            sleeve = 'LongSleeve' if res[3] > res[2] else 'ShortSleeve'
+            upper_label += ' {}'.format(sleeve)
+            upper_res = res[4:8]
+            if np.max(upper_res) > self.threshold:
+                upper_label += ' {}'.format(upper_list[np.argmax(upper_res)])
+            label_res.append(upper_label)
+            # lower
+            lower_res = res[8:14]
+            lower_label = 'Lower: '
+            has_lower = False
+            for i, l in enumerate(lower_res):
+                if l > self.threshold:
+                    lower_label += ' {}'.format(lower_list[i])
+                    has_lower = True
+            if not has_lower:
+                lower_label += ' {}'.format(lower_list[np.argmax(lower_res)])
+
+            label_res.append(lower_label)
+            # shoe
+            shoe = 'Boots' if res[14] > self.threshold else 'No boots'
+            label_res.append(shoe)
+
+            batch_res.append(label_res)
+        result = {'output': batch_res}
+        return result
+```
-- 
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