def download_and_classify_image(image_url):
global images_classified
if images_classified >= settings.MAX_IMAGES_PER_PAGE:
return
downloads_folder = settings.DOWNLOADS_FOLDER
# Prevent file conflicts by using unique identifiers
hex_name = 'temp_image_%s' % uuid.uuid4().hex
hex_name_png = hex_name + '.png'
hex_name_jpg = hex_name + '.jpg'
# Save all images as a "png", but then convert them all to "jpg"
web_core.save_file_as(image_url, hex_name_png)
image_base.convert_image_file_to_jpg(
"%s/%s" % (downloads_folder, hex_name_png))
# "deleting" files without filling up your recycle bin
lock2.acquire()
os.rename(downloads_folder + "/" + hex_name_png,
downloads_folder + "/temp_image_png.png")
lock2.release()
# Classify the image if it's larger than the minimum size
width, height = image_base.get_image_file_dimensions(
"%s/%s" % (downloads_folder, hex_name_jpg))
best_guess = None
if width >= settings.MIN_W_H and height >= settings.MIN_W_H:
best_guess = classify_image.external_run(
"%s/%s" % (downloads_folder, hex_name_jpg))
lock1.acquire()
if images_classified == 0:
print("\n*** "
"Classifying all eligible page images:"
" ***")
images_classified += 1
lock1.release()
best_guess = best_guess.strip()
print(best_guess)
# "deleting" files without filling up your recycle bin
lock3.acquire()
os.rename(downloads_folder + '/' + hex_name_jpg,
downloads_folder + "/temp_image_jpg.jpg")
lock3.release()
def main():
expected_arg = "[A valid PAGE_URL or IMAGE_URL]"
num_args = len(sys.argv)
if num_args < 2 or num_args > 2:
print "\n* INVALID RUN COMMAND! * Usage:"
print "classify %s\n" % expected_arg
elif num_args == 2:
url = sys.argv[1]
valid_url = web_core.is_valid_url(url)
if not valid_url:
file_path = url
if isfile(file_path):
best_guess = image_base.classify_local_image(file_path)
elif isdir(file_path):
best_guess = image_base.classify_folder_images(
file_path, return_dict=True)
else:
raise Exception("Error: %s is not a valid image path!" % url)
print("\n*** Best match classification: ***")
print(best_guess)
print("")
return
content_type = web_core.get_content_type(url)
if content_type == 'other':
raise Exception("Error: %s does not evaluate to %s" %
(url, expected_arg))
elif content_type == 'image':
best_guess = image_base.classify_image_url(url)
print("\n*** Best match classification: ***")
print(best_guess)
print("")
elif content_type == 'html':
global images_classified
image_list = image_base.get_all_images_on_page(url)
if 'linux2' not in sys.platform and settings.MAX_THREADS > 1:
# Multi-threading the work when not using Docker Linux
pool = ThreadPool(settings.MAX_THREADS)
pool.map(download_and_classify_image, image_list)
pool.close()
pool.join()
else:
# Single-threading the image classification work
min_w_h = settings.MIN_W_H # Minimum size for classification
for image in image_list:
web_core.save_file_as(image, "temp_image.png")
image_base.convert_image_file_to_jpg(
"downloads_folder/temp_image.png")
width, height = image_base.get_image_file_dimensions(
"downloads_folder/temp_image.jpg")
if width >= min_w_h and height >= min_w_h:
best_guess = classify_image.external_run(
"downloads_folder/temp_image.jpg")
if images_classified == 0:
print(
"\n*** "
"Best match classifications for page images:"
" ***")
images_classified += 1
print best_guess
if images_classified >= settings.MAX_IMAGES_PER_PAGE:
break
if images_classified >= settings.MAX_IMAGES_PER_PAGE:
print(
"\n(NOTE: Exceeded page classification limit "
"of %d images per URL! Stopping early.)" %
(settings.MAX_IMAGES_PER_PAGE))
if images_classified == 0:
print(
"\nCould not find images to classify on the page! "
"(Min size = %dx%d pixels)" %
(settings.MIN_W_H, settings.MIN_W_H))
print("")
else:
raise Exception("Unexpected content type %s. Fix the code!" %
content_type)