Refine readme for cycle_gan (#2420)

1.Modify the checkpoint save path
2. Modifiy the img save paht
3. Synchronous modification for Readme
4. update generated result img

dygraph/cycle_gan/README.md

@@ -88,6 +88,7 @@ todo：loss曲线
 ```
 env CUDA_VISIBLE_DEVICES=0 python test.py --epoch=200
 ```
+生成结果在 `output_0/eval`中
 
 
 ### 预测
@@ -98,7 +99,7 @@ env CUDA_VISIBLE_DEVICES=0 python test.py --epoch=200
 
 ```
 env CUDA_VISIBLE_DEVICES=0 python infer.py \
-    --init_model="./G/199" --input="./image/testA/123_A.jpg" \
+    --init_model="./output_0/checkpoints/199" --input="./image/testA/123_A.jpg" \
     --input_style=A 
 ```
 
@@ -106,9 +107,10 @@ env CUDA_VISIBLE_DEVICES=0 python infer.py \
 
 ```
 env CUDA_VISIBLE_DEVICES=0 python infer.py \
-    --init_model="./G/199" --input="./image/testB/78_B.jpg" \
+    --init_model="./output_0/checkpoints/199" --input="./image/testB/78_B.jpg" \
     --input_style=B 
 ```
+生成结果在 `output_0/single`中
 
 训练180轮的模型预测效果如fakeA和fakeB所示：
 

dygraph/cycle_gan/infer.py

@@ -25,15 +25,15 @@ add_arg = functools.partial(add_arguments, argparser=parser)
 
 
 # yapf: disable
-add_arg('input',             str,   "123_A.jpg",      "input image")
+add_arg('input',             str,   "./image/testA/123_A.jpg",      "input image")
 add_arg('output',            str,   "./output_0", "The directory the model and the test result to be saved to.")
-add_arg('init_model',        str,   './G/150',       "The init model file of directory.")
+add_arg('init_model',        str,   './output_0/checkpoints/0',       "The init model file of directory.")
 add_arg('input_style',       str,   "A",        "A or B")
 def infer():
     with fluid.dygraph.guard():
         data_shape = [-1,3,256,256]
        
-        out_path = args.output + "/single" + "/" + str(args.input)
+        out_path = args.output + "/single"
         if not os.path.exists(out_path):
             os.makedirs(out_path)
         cycle_gan = Cycle_Gan("cycle_gan")

dygraph/cycle_gan/test.py

@@ -25,7 +25,7 @@ add_arg = functools.partial(add_arguments, argparser=parser)
 add_arg('batch_size',        int,   1,          "Minibatch size.")
 add_arg('epoch',             int,   None,        "The number of weights to be testes.")
 add_arg('output',            str,   "./output_0", "The directory the model and the test result to be saved to.")
-add_arg('init_model',        str,   './G/',       "The init model file of directory.")
+add_arg('init_model',        str,   './output_0/checkpoints/',       "The init model file of directory.")
 
 def test():
     with fluid.dygraph.guard():