Merge pull request #167 from masa-su/feature/tutorial_readme

added readme
masa-su · Feb 26, 2021 · dd6af82 · dd6af82
2 parents 23049ba + 9063894
commit dd6af82
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diff --git a/tutorial/English/04-DeepMarkovModel.ipynb b/tutorial/English/04-DeepMarkovModel.ipynb
diff --git a/tutorial/English/utils.py b/tutorial/English/utils.py
@@ -23,21 +23,65 @@ def __init__(self, pickle_path="cartpole_28.pickle"):
         # episode_frames: np.array([episode_num, one_episode_length, height, width, Channels]) (10000, 30, 28, 28, 3)
         # actions:             np.array([episode_num, one_episode_length]) (10000, 30)
         # HWC → CHW
-        episode_frames = episode_frames.transpose(0, 1, 4, 2, 3)
+        episode_frames = episode_frames.transpose(0, 1, 4, 2, 3) / 1.0
+        # print(episode_frames.dtype)
         actions = actions[:, :, np.newaxis]
 
         self.episode_frames = torch.from_numpy(episode_frames.astype(np.float32))
         self.actions = torch.from_numpy(actions.astype(np.float32))
+
+        self.mean = torch.zeros_like(self.episode_frames[0])
+        self.std = torch.zeros_like(self.episode_frames[0])
+
+        self.mean[:, 0, :, :] = 182.6091
+        self.mean[:, 1, :, :] = 182.6091
+        self.mean[:, 2, :, :] = 182.6091
+
+        self.std[:, 0, :, :] = 45.5565
+        self.std[:, 1, :, :] = 47.6260
+        self.std[:, 2, :, :] = 50.7284
 
     def __len__(self):
         return len(self.episode_frames)
 
     def __getitem__(self, idx):
         return {
-            "episode_frames": self.episode_frames[idx] / 255,
+            "episode_frames": (self.episode_frames[idx] - self.mean) / self.std,
             "actions": self.actions[idx]
         }
+
+    def _calculate_mean_std(self):
+        print(self.episode_frames.shape)
+        std = torch.std(self.episode_frames, dim=(0, 1, 3, 4))
+        mean = torch.mean(self.episode_frames, dim=(0, 1, 3, 4))
+        print("mean: ", mean)
+        print(mean.shape)
+        print("std: ", std)
+        print(std.shape)
+        # mean:  tensor([182.6091, 182.6091, 182.6091])
+        # torch.Size([3])
+        # std:  tensor([45.5565, 47.6260, 50.7284])
+        # torch.Size([3])
+
+
+def postprocess(image):
+    image_ = image.detach().clone()
+    # print(image_.shape)
+    mean = torch.ones_like(image_)
+    std = torch.ones_like(image_)
+    mean[:, 0, :, :] = 182.6091
+    mean[:, 1, :, :] = 182.6091
+    mean[:, 2, :, :] = 182.6091
+
+    std[:, 0, :, :] = 45.5565
+    std[:, 1, :, :] = 47.6260
+    std[:, 2, :, :] = 50.7284
+
+    image_ = image_ * std + mean
+    image_ = torch.clamp(image_, min=0.0, max=255.0) / 255.
+    return image_
 
 
 if __name__ == "__main__":
-    pass
+    data_set = DMMDataset()
+    data_set._calculate_mean_std()