From 56284eda83220d429eb0549424d48a4cac3f76f3 Mon Sep 17 00:00:00 2001
From: liaogang <liaogang@baidu.com>
Date: Fri, 21 Apr 2017 19:41:55 +0800
Subject: [PATCH] Add python current path for inference

---
 02.recognize_digits/README.en.md      | 5 ++++-
 02.recognize_digits/README.md         | 5 ++++-
 02.recognize_digits/index.en.html     | 5 ++++-
 02.recognize_digits/index.html        | 5 ++++-
 02.recognize_digits/train.py          | 4 +++-
 03.image_classification/README.en.md  | 4 +++-
 03.image_classification/README.md     | 4 +++-
 03.image_classification/index.en.html | 4 +++-
 03.image_classification/index.html    | 4 +++-
 03.image_classification/train.py      | 4 +++-
 10 files changed, 34 insertions(+), 10 deletions(-)

diff --git a/02.recognize_digits/README.en.md b/02.recognize_digits/README.en.md
index faa20b3..894d4fa 100644
--- a/02.recognize_digits/README.en.md
+++ b/02.recognize_digits/README.en.md
@@ -321,14 +321,17 @@ After training is done, user can use the trained model to classify images. The f
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file).convert('L')
     im = im.resize((28, 28), Image.ANTIALIAS)
     im = np.array(im).astype(np.float32).flatten()
     im = im / 255.0
     return im
+
 test_data = []
-test_data.append((load_image('image/infer_3.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/infer_3.png'),))
 
 probs = paddle.infer(
     output_layer=predict, parameters=parameters, input=test_data)
diff --git a/02.recognize_digits/README.md b/02.recognize_digits/README.md
index 5635900..edb8072 100644
--- a/02.recognize_digits/README.md
+++ b/02.recognize_digits/README.md
@@ -317,14 +317,17 @@ trainer.train(
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file).convert('L')
     im = im.resize((28, 28), Image.ANTIALIAS)
     im = np.array(im).astype(np.float32).flatten()
     im = im / 255.0
     return im
+
 test_data = []
-test_data.append((load_image('image/infer_3.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/infer_3.png'),))
 
 probs = paddle.infer(
     output_layer=predict, parameters=parameters, input=test_data)
diff --git a/02.recognize_digits/index.en.html b/02.recognize_digits/index.en.html
index a9daec9..53895ea 100644
--- a/02.recognize_digits/index.en.html
+++ b/02.recognize_digits/index.en.html
@@ -363,14 +363,17 @@ After training is done, user can use the trained model to classify images. The f
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file).convert('L')
     im = im.resize((28, 28), Image.ANTIALIAS)
     im = np.array(im).astype(np.float32).flatten()
     im = im / 255.0
     return im
+
 test_data = []
-test_data.append((load_image('image/infer_3.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/infer_3.png'),))
 
 probs = paddle.infer(
     output_layer=predict, parameters=parameters, input=test_data)
diff --git a/02.recognize_digits/index.html b/02.recognize_digits/index.html
index e9c3d40..82593db 100644
--- a/02.recognize_digits/index.html
+++ b/02.recognize_digits/index.html
@@ -359,14 +359,17 @@ trainer.train(
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file).convert('L')
     im = im.resize((28, 28), Image.ANTIALIAS)
     im = np.array(im).astype(np.float32).flatten()
     im = im / 255.0
     return im
+
 test_data = []
-test_data.append((load_image('image/infer_3.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/infer_3.png'),))
 
 probs = paddle.infer(
     output_layer=predict, parameters=parameters, input=test_data)
diff --git a/02.recognize_digits/train.py b/02.recognize_digits/train.py
index ec285a3..e55752c 100644
--- a/02.recognize_digits/train.py
+++ b/02.recognize_digits/train.py
@@ -1,4 +1,5 @@
 import gzip
+import os
 from PIL import Image
 import numpy as np
 import paddle.v2 as paddle
@@ -114,7 +115,8 @@ def main():
         return im
 
     test_data = []
-    test_data.append((load_image('image/infer_3.png'), ))
+    cur_dir = os.path.dirname(os.path.realpath(__file__))
+    test_data.append((load_image(cur_dir + '/image/infer_3.png'), ))
 
     probs = paddle.infer(
         output_layer=predict, parameters=parameters, input=test_data)
diff --git a/03.image_classification/README.en.md b/03.image_classification/README.en.md
index d5e8b65..93391af 100644
--- a/03.image_classification/README.en.md
+++ b/03.image_classification/README.en.md
@@ -488,6 +488,7 @@ After training is done, users can use the trained model to classify images. The
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file)
     im = im.resize((32, 32), Image.ANTIALIAS)
@@ -495,7 +496,8 @@ def load_image(file):
     im = im / 255.0
     return im
 test_data = []
-test_data.append((load_image('image/dog.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/dog.png'),)
 
 probs = paddle.infer(
     output_layer=out, parameters=parameters, input=test_data)
diff --git a/03.image_classification/README.md b/03.image_classification/README.md
index 8f3a8d2..96891b1 100644
--- a/03.image_classification/README.md
+++ b/03.image_classification/README.md
@@ -480,6 +480,7 @@ Test with Pass 0, {'classification_error_evaluator': 0.885200023651123}
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file)
     im = im.resize((32, 32), Image.ANTIALIAS)
@@ -487,7 +488,8 @@ def load_image(file):
     im = im / 255.0
     return im
 test_data = []
-test_data.append((load_image('image/dog.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/dog.png'),)
 
 probs = paddle.infer(
     output_layer=out, parameters=parameters, input=test_data)
diff --git a/03.image_classification/index.en.html b/03.image_classification/index.en.html
index 37f1dc5..b737fb7 100644
--- a/03.image_classification/index.en.html
+++ b/03.image_classification/index.en.html
@@ -530,6 +530,7 @@ After training is done, users can use the trained model to classify images. The
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file)
     im = im.resize((32, 32), Image.ANTIALIAS)
@@ -537,7 +538,8 @@ def load_image(file):
     im = im / 255.0
     return im
 test_data = []
-test_data.append((load_image('image/dog.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/dog.png'),)
 
 probs = paddle.infer(
     output_layer=out, parameters=parameters, input=test_data)
diff --git a/03.image_classification/index.html b/03.image_classification/index.html
index 4001d12..25373fb 100644
--- a/03.image_classification/index.html
+++ b/03.image_classification/index.html
@@ -522,6 +522,7 @@ Test with Pass 0, {'classification_error_evaluator': 0.885200023651123}
 ```python
 from PIL import Image
 import numpy as np
+import os
 def load_image(file):
     im = Image.open(file)
     im = im.resize((32, 32), Image.ANTIALIAS)
@@ -529,7 +530,8 @@ def load_image(file):
     im = im / 255.0
     return im
 test_data = []
-test_data.append((load_image('image/dog.png'),))
+cur_dir = os.path.dirname(os.path.realpath(__file__))
+test_data.append((load_image(cur_dir + '/image/dog.png'),)
 
 probs = paddle.infer(
     output_layer=out, parameters=parameters, input=test_data)
diff --git a/03.image_classification/train.py b/03.image_classification/train.py
index e60b9bd..9ec8237 100644
--- a/03.image_classification/train.py
+++ b/03.image_classification/train.py
@@ -94,6 +94,7 @@ def main():
     # inference
     from PIL import Image
     import numpy as np
+    import os
 
     def load_image(file):
         im = Image.open(file)
@@ -103,7 +104,8 @@ def main():
         return im
 
     test_data = []
-    test_data.append((load_image('image/dog.png'), ))
+    cur_dir = os.path.dirname(os.path.realpath(__file__))
+    test_data.append((load_image(cur_dir + '/image/dog.png'), ))
 
     probs = paddle.infer(
         output_layer=out, parameters=parameters, input=test_data)
-- 
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