Added .caffemodel files downloader for tests on post-build step.

modules/dnn/CMakeLists.txt

@@ -33,9 +33,18 @@ ocv_module_include_directories(include src/caffe ${PROTOBUF_INCLUDE_DIR})
 
 ocv_create_module(${PROTOBUF_LIBRARIES})
 
+ocv_add_samples()
 ocv_add_accuracy_tests()
 ocv_add_perf_tests()
-ocv_add_samples()
+
+OCV_OPTION(${the_module}_DOWNLOAD_CAFFE_MODELS "Use GoogLeNet Caffe model for testing" ON IF BUILD_TESTS AND PYTHON2_EXECUTABLE AND DEFINED ENV{OPENCV_TEST_DATA_PATH})
+if(BUILD_TESTS AND ${the_module}_DOWNLOAD_CAFFE_MODELS)
+    add_custom_command( TARGET opencv_test_${name} POST_BUILD
+                        COMMAND ${PYTHON2_EXECUTABLE} download_model.py test_models.json
+                        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/scripts )
+else()
+    add_definitions(-DDISABLE_CAFFE_MODEL_TESTS=1)
+endif()
 
 else()#build as standalone module (for development purposes)
 

modules/dnn/scripts/download_model.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+import os
+import sys
+import time
+import urllib
+import hashlib
+import argparse
+import json
+
+
+def reporthook(count, block_size, total_size):
+    """
+    From http://blog.moleculea.com/2012/10/04/urlretrieve-progres-indicator/
+    """
+    global start_time
+    if count == 0:
+        start_time = time.time()
+        return
+    duration = time.time() - start_time
+    progress_size = int(count * block_size)
+    speed = int(progress_size / (1024 * duration))
+    percent = int(count * block_size * 100 / total_size)
+    sys.stdout.write("\r...%d%%, %d MB, %d KB/s, %d seconds passed" %
+                    (percent, progress_size / (1024 * 1024), speed, duration))
+    sys.stdout.flush()
+
+# Closure-d function for checking SHA1.
+def model_checks_out(filename, sha1):
+    with open(filename, 'r') as f:
+        return hashlib.sha1(f.read()).hexdigest() == sha1
+
+def model_download(filename, url, sha1):
+    # Check if model exists.
+    if os.path.exists(filename) and model_checks_out(filename, sha1):
+        print("Model {} already exists.".format(filename))
+        return
+    
+    # Download and verify model.
+    urllib.urlretrieve(url, filename, reporthook)
+    if not model_checks_out():
+        print("ERROR: model {} did not download correctly!".format(url))
+        sys.exit(1)
+    
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description="Downloading trained model binaries.")
+    parser.add_argument("download_list")
+    args = parser.parse_args()
+
+    test_dir = os.environ.get("OPENCV_TEST_DATA_PATH")
+    if not test_dir:
+        print "ERROR: OPENCV_TEST_DATA_PATH environment not specified"
+        sys.exit(1)
+    
+    try:
+        with open(args.download_list, 'r') as f:
+            models_to_download = json.load(f)
+    except:
+        print "ERROR: Can't pasrse {}".format(args.download_list)
+        sys.exit(1)
+        
+    for model_name in models_to_download:
+        model = models_to_download[model_name]
+        
+        dst_dir = os.path.join(test_dir, os.path.dirname(model['file']))
+        dst_file = os.path.join(test_dir, model['file'])
+        if not os.path.exists(dst_dir):
+            print "ERROR: Can't find module testdata path '{}'".format(dst_dir)
+            sys.exit(1)
+            
+        print "Downloading model '{}' to {} from {} ...".format(model_name, dst_file, model['url'])
+        model_download(dst_file, model['url'], model['sha1'])

modules/dnn/scripts/test_models.json

@@ -0,0 +1,7 @@
+{
+  "googlenet": {
+    "file": "dnn/bvlc_googlenet.caffemodel",
+    "url": "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel",
+    "sha1": "d41971236422c20b1d7d92769670f3642ef4611a"
+  }
+}