fix fid (PaddlePaddle#336)

* fix fid * fix fid * add pixel2pixel facades model
AnnaTrainingG · Jun 4, 2021 · 1f335bb · 1f335bb
1 parent bab376f
commit 1f335bb
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Showing 7 changed files with 55 additions and 10 deletions.
diff --git a/configs/pix2pix_cityscapes.yaml b/configs/pix2pix_cityscapes.yaml
@@ -107,3 +107,13 @@ log_config:
 
 snapshot_config:
   interval: 5
+
+validate:
+  interval: 500
+  save_img: false
+  metrics:
+    fid: # metric name, can be arbitrary
+        name: FID
+        batch_size: 8
+
+
diff --git a/configs/pix2pix_cityscapes_2gpus.yaml b/configs/pix2pix_cityscapes_2gpus.yaml
@@ -107,3 +107,13 @@ log_config:
 
 snapshot_config:
   interval: 5
+
+validate:
+  interval: 500
+  save_img: false
+  metrics:
+    fid: # metric name, can be arbitrary
+        name: FID
+        batch_size: 8
+
+
diff --git a/configs/pix2pix_facades.yaml b/configs/pix2pix_facades.yaml
@@ -107,3 +107,13 @@ log_config:
 
 snapshot_config:
   interval: 5
+
+validate:
+  interval: 500
+  save_img: false
+  metrics:
+    fid: # metric name, can be arbitrary
+        name: FID
+        batch_size: 8
+
+
diff --git a/docs/en_US/tutorials/pix2pix_cyclegan.md b/docs/en_US/tutorials/pix2pix_cyclegan.md
@@ -43,6 +43,7 @@
 | 模型 | 数据集 | 下载地址 |
 |---|---|---|
 | Pix2Pix_cityscapes  | cityscapes | [Pix2Pix_cityscapes](https://paddlegan.bj.bcebos.com/models/Pix2Pix_cityscapes.pdparams)
+| Pix2Pix_facedes     | facades    | [Pix2Pix_facades](https://paddlegan.bj.bcebos.com/models/Pixel2Pixel_facades.pdparams)
 
 
 

diff --git a/docs/zh_CN/tutorials/pix2pix_cyclegan.md b/docs/zh_CN/tutorials/pix2pix_cyclegan.md
@@ -44,6 +44,7 @@
 | 模型 | 数据集 | 下载地址 |
 |---|---|---|
 | Pix2Pix_cityscapes  | cityscapes | [Pix2Pix_cityscapes](https://paddlegan.bj.bcebos.com/models/Pix2Pix_cityscapes.pdparams)
+| Pix2Pix_facedes     | facades    | [Pix2Pix_facades](https://paddlegan.bj.bcebos.com/models/Pixel2Pixel_facades.pdparams)
 
 
 # 2 CycleGAN

diff --git a/ppgan/metrics/fid.py b/ppgan/metrics/fid.py
@@ -53,21 +53,30 @@ def __init__(self, batch_size=1, use_GPU=True, dims = 2048, premodel_path=None,
             premodel_path = get_weights_path_from_url(INCEPTIONV3_WEIGHT_URL)
         self.model = model
         param_dict = paddle.load(premodel_path)
-        model.load_dict(param_dict)
-        model.eval()
+        self.model.load_dict(param_dict)
+        self.model.eval()
         self.reset()   
 
     def reset(self):
+        self.preds = []
+        self.gts = []
         self.results = []
 
     def update(self, preds, gts):
-        value = calculate_fid_given_img(preds, gts, self.batch_size, self.model, self.use_GPU, self.dims)
-        self.results.append(value)
-
+        if len(preds.shape) >=4:
+            self.preds.append(preds)
+            self.gts.append(gts)
+        else:
+            for i in range(preds.shape[0]):
+                self.preds.append(preds[i,:,:,:,:])
+                self.gts.append(gts[i,:,:,:,:])
+
     def accumulate(self):
-        if len(self.results) <= 0:
-            return 0.
-        return np.mean(self.results)
+        self.preds = paddle.concat(self.preds, axis=0)
+        self.gts = paddle.concat(self.gts, axis=0)
+        value = calculate_fid_given_img(self.preds, self.gts, self.batch_size, self.model, self.use_GPU, self.dims)
+        self.reset() 
+        return value
 
     def name(self):
         return 'FID'
@@ -123,7 +132,6 @@ def _get_activations_from_ims(img, model, batch_size, dims, use_gpu):
         images = img[start:end]
         if images.shape[1] != 3:
             images = images.transpose((0, 3, 1, 2))
-        images /= 255
 
         images = paddle.to_tensor(images)
         pred = model(images)[0][0]

diff --git a/ppgan/models/pix2pix_model.py b/ppgan/models/pix2pix_model.py
@@ -141,5 +141,10 @@ def train_iter(self, optimizers=None):
         optimizers['optimG'].step()
 
     def test_iter(self, metrics=None):
+        self.nets['netG'].eval()
+        self.forward()
         with paddle.no_grad():
-            self.forward()
+            if metrics is not None:
+                for metric in metrics.values():
+                    metric.update(self.fake_B, self.real_B)
+        self.nets['netG'].train()