summaryrefslogtreecommitdiff
path: root/examples
diff options
context:
space:
mode:
authorEvan Shelhamer <shelhamer@imaginarynumber.net>2015-03-06 19:36:29 -0800
committerEvan Shelhamer <shelhamer@imaginarynumber.net>2015-03-08 00:16:27 -0800
commit5c84795572cf08f020dab31af43e7d8478628f44 (patch)
treead9a7229b3ab68eb2952293faa216d74cfefc729 /examples
parent0b398925d94df4445a6cf28c30cdf2802260903a (diff)
downloadcaffeonacl-5c84795572cf08f020dab31af43e7d8478628f44.tar.gz
caffeonacl-5c84795572cf08f020dab31af43e7d8478628f44.tar.bz2
caffeonacl-5c84795572cf08f020dab31af43e7d8478628f44.zip
[pycaffe] align web demo with #1728 and #1902
Diffstat (limited to 'examples')
-rw-r--r--examples/web_demo/app.py14
1 files changed, 9 insertions, 5 deletions
diff --git a/examples/web_demo/app.py b/examples/web_demo/app.py
index e456526f..208b1da0 100644
--- a/examples/web_demo/app.py
+++ b/examples/web_demo/app.py
@@ -10,12 +10,13 @@ import tornado.wsgi
import tornado.httpserver
import numpy as np
import pandas as pd
-from PIL import Image as PILImage
+import Image
import cStringIO as StringIO
import urllib
-import caffe
import exifutil
+import caffe
+
REPO_DIRNAME = os.path.abspath(os.path.dirname(__file__) + '/../..')
UPLOAD_FOLDER = '/tmp/caffe_demos_uploads'
ALLOWED_IMAGE_EXTENSIONS = set(['png', 'bmp', 'jpg', 'jpe', 'jpeg', 'gif'])
@@ -80,7 +81,7 @@ def classify_upload():
def embed_image_html(image):
"""Creates an image embedded in HTML base64 format."""
- image_pil = PILImage.fromarray((255 * image).astype('uint8'))
+ image_pil = Image.fromarray((255 * image).astype('uint8'))
image_pil = image_pil.resize((256, 256))
string_buf = StringIO.StringIO()
image_pil.save(string_buf, format='png')
@@ -114,15 +115,18 @@ class ImagenetClassifier(object):
"File for {} is missing. Should be at: {}".format(key, val))
default_args['image_dim'] = 256
default_args['raw_scale'] = 255.
- default_args['gpu_mode'] = False
def __init__(self, model_def_file, pretrained_model_file, mean_file,
raw_scale, class_labels_file, bet_file, image_dim, gpu_mode):
logging.info('Loading net and associated files...')
+ if gpu_mode:
+ caffe.set_mode_gpu()
+ else:
+ caffe.set_mode_cpu()
self.net = caffe.Classifier(
model_def_file, pretrained_model_file,
image_dims=(image_dim, image_dim), raw_scale=raw_scale,
- mean=np.load(mean_file), channel_swap=(2, 1, 0), gpu=gpu_mode
+ mean=np.load(mean_file).mean(1).mean(1), channel_swap=(2, 1, 0)
)
with open(class_labels_file) as f: