def wrap_with_abbreviation(abbr, text, syntax='html', profile='plain'):
"""
Wraps passed text with abbreviation. Text will be placed inside last
expanded element
@param abbr: Abbreviation
@type abbr: str
@param text: Text to wrap
@type text: str
@param syntax: Document type (html, xml, etc.)
@type syntax: str
@param profile: Output profile's name.
@type profile: str
@return {String}
"""
tree_root = utils.parse_into_tree(abbr, syntax)
pasted = False
if tree_root:
if tree_root.multiply_elem:
# we have a repeating element, put content in
tree_root.multiply_elem.set_paste_content(text)
tree_root.multiply_elem.repeat_by_lines = pasted = True
tree = utils.rollout_tree(tree_root)
if not pasted:
tree.paste_content(text)
utils.apply_filters(tree, syntax, profile, tree_root.filters)
return utils.replace_variables(tree.to_string())
return None
def wrap_with_abbreviation(abbr, text, syntax="html", profile="plain"):
"""
Wraps passed text with abbreviation. Text will be placed inside last
expanded element
@param abbr: Abbreviation
@type abbr: str
@param text: Text to wrap
@type text: str
@param syntax: Document type (html, xml, etc.)
@type syntax: str
@param profile: Output profile's name.
@type profile: str
@return {String}
"""
tree_root = utils.parse_into_tree(abbr, syntax)
pasted = False
if tree_root:
if tree_root.multiply_elem:
# we have a repeating element, put content in
tree_root.multiply_elem.set_paste_content(text)
tree_root.multiply_elem.repeat_by_lines = pasted = True
tree = utils.rollout_tree(tree_root)
if not pasted:
tree.paste_content(text)
utils.apply_filters(tree, syntax, profile, tree_root.filters)
return utils.replace_variables(tree.to_string())
return None
def apply_actions_on_image(session_id, action_stack, filename,
image_signature):
action_stack = deepcopy(action_stack)
# If we have arrived to the original image
if len(action_stack) == 0:
return im_pil0
# Pop out the last action
last_action = action_stack.pop()
# Apply all the previous action_stack, and gets the image PIL
im_pil = apply_actions_on_image(session_id, action_stack, filename,
image_signature)
im_size = im_pil.size
# Apply the rest of the action_stack
operation = last_action['operation']
selectedData = last_action['selectedData']
type = last_action['type']
# Select using Lasso
if selectedData and 'lassoPoints' in selectedData:
selection_mode = 'lasso'
selection_zone = generate_lasso_mask(im_pil, selectedData)
# Select using rectangular box
elif selectedData and 'range' in selectedData:
selection_mode = 'select'
lower, upper = map(int, selectedData['range']['y'])
left, right = map(int, selectedData['range']['x'])
# Adjust height difference
height = im_size[1]
upper = height - upper
lower = height - lower
selection_zone = (left, upper, right, lower)
# Select the whole image
else:
selection_mode = 'select'
selection_zone = (0, 0) + im_size
# Apply the filters
if type == 'filter':
apply_filters(image=im_pil,
zone=selection_zone,
filter=operation,
mode=selection_mode)
elif type == 'enhance':
enhancement = operation['enhancement']
factor = operation['enhancement_factor']
apply_enhancements(image=im_pil,
zone=selection_zone,
enhancement=enhancement,
enhancement_factor=factor,
mode=selection_mode)
return im_pil
def expand_abbreviation(abbr, syntax='html', profile_name='plain'): """ Expands abbreviation into a XHTML tag string @type abbr: str @return: str """ tree_root = utils.parse_into_tree(abbr, syntax) if tree_root: tree = utils.rollout_tree(tree_root) utils.apply_filters(tree, syntax, profile_name, tree_root.filters) return utils.replace_variables(tree.to_string()) return ''
def expand_abbreviation(abbr, syntax='html', profile_name='plain'): """ Expands abbreviation into a XHTML tag string @type abbr: str @return: str """ tree_root = utils.parse_into_tree(abbr, syntax) if tree_root: tree = utils.rollout_tree(tree_root) utils.apply_filters(tree, syntax, profile_name, tree_root.filters) return utils.replace_variables(tree.to_string()) return ''
def generic_post_list_renderer(self, lang, posts, output_name,
template_name, filters, extra_context):
"""Renders pages with lists of posts."""
deps = self.template_system.template_deps(template_name)
for post in posts:
deps += post.deps(lang)
context = {}
context["posts"] = posts
context["title"] = self.config['BLOG_TITLE']
context["description"] = self.config['BLOG_DESCRIPTION']
context["lang"] = lang
context["prevlink"] = None
context["nextlink"] = None
context.update(extra_context)
deps_context = copy(context)
deps_context["posts"] = [(p.titles[lang], p.permalink(lang))
for p in posts]
deps_context["global"] = self.config['GLOBAL_CONTEXT']
task = {
'name':
output_name.encode('utf8'),
'targets': [output_name],
'file_dep':
deps,
'actions':
[(self.render_template, [template_name, output_name, context])],
'clean':
True,
'uptodate': [config_changed(deps_context)]
}
yield utils.apply_filters(task, filters)
def generic_post_list_renderer(self, lang, posts,
output_name, template_name, filters, extra_context):
"""Renders pages with lists of posts."""
deps = self.template_system.template_deps(template_name)
for post in posts:
deps += post.deps(lang)
context = {}
context["posts"] = posts
context["title"] = self.config['BLOG_TITLE']
context["description"] = self.config['BLOG_DESCRIPTION']
context["lang"] = lang
context["prevlink"] = None
context["nextlink"] = None
context.update(extra_context)
deps_context = copy(context)
deps_context["posts"] = [(p.titles[lang], p.permalink(lang))
for p in posts]
task = {
'name': output_name.encode('utf8'),
'targets': [output_name],
'file_dep': deps,
'actions': [(self.render_template,
[template_name, output_name, context])],
'clean': True,
'uptodate': [config_changed(deps_context)]
}
yield utils.apply_filters(task, filters)
def generic_page_renderer(self, lang, wildcard, template_name, destination,
filters):
"""Render post fragments to final HTML pages."""
for post in glob.glob(wildcard):
post_name = os.path.splitext(post)[0]
context = {}
post = self.global_data[post_name]
deps = post.deps(lang) + \
self.template_system.template_deps(template_name)
context['post'] = post
context['lang'] = lang
context['title'] = post.title(lang)
context['description'] = post.description(lang)
context['permalink'] = post.permalink(lang)
context['page_list'] = self.pages
output_name = os.path.join(self.config['OUTPUT_FOLDER'],
self.config['TRANSLATIONS'][lang],
destination,
post.pagenames[lang] + ".html")
deps_dict = copy(context)
deps_dict.pop('post')
if post.prev_post:
deps_dict['PREV_LINK'] = [post.prev_post.permalink(lang)]
if post.next_post:
deps_dict['NEXT_LINK'] = [post.next_post.permalink(lang)]
deps_dict['OUTPUT_FOLDER'] = self.config['OUTPUT_FOLDER']
deps_dict['TRANSLATIONS'] = self.config['TRANSLATIONS']
deps_dict['global'] = self.config['GLOBAL_CONTEXT']
task = {
'name':
output_name.encode('utf-8'),
'file_dep':
deps,
'targets': [output_name],
'actions':
[(self.render_template, [template_name, output_name,
context])],
'clean':
True,
'uptodate': [config_changed(deps_dict)],
}
yield utils.apply_filters(task, filters)
def generic_page_renderer(self, lang, wildcard,
template_name, destination, filters):
"""Render post fragments to final HTML pages."""
for post in glob.glob(wildcard):
post_name = os.path.splitext(post)[0]
context = {}
post = self.global_data[post_name]
deps = post.deps(lang) + \
self.template_system.template_deps(template_name)
context['post'] = post
context['lang'] = lang
context['title'] = post.title(lang)
context['description'] = post.description(lang)
context['permalink'] = post.permalink(lang)
context['page_list'] = self.pages
output_name = os.path.join(
self.config['OUTPUT_FOLDER'],
self.config['TRANSLATIONS'][lang],
destination,
post.pagenames[lang] + ".html")
deps_dict = copy(context)
deps_dict.pop('post')
if post.prev_post:
deps_dict['PREV_LINK'] = [post.prev_post.permalink(lang)]
if post.next_post:
deps_dict['NEXT_LINK'] = [post.next_post.permalink(lang)]
deps_dict['OUTPUT_FOLDER'] = self.config['OUTPUT_FOLDER']
deps_dict['TRANSLATIONS'] = self.config['TRANSLATIONS']
deps_dict['global'] = self.config['GLOBAL_CONTEXT']
task = {
'name': output_name.encode('utf-8'),
'file_dep': deps,
'targets': [output_name],
'actions': [(self.render_template,
[template_name, output_name, context])],
'clean': True,
'uptodate': [config_changed(deps_dict)],
}
yield utils.apply_filters(task, filters)
def generic_page_renderer(self, lang, wildcard, template_name, destination, filters):
"""Render post fragments to final HTML pages."""
for post in glob.glob(wildcard):
post_name = os.path.splitext(post)[0]
context = {}
post = self.global_data[post_name]
deps = post.deps(lang) + self.template_system.template_deps(template_name)
context["post"] = post
context["lang"] = lang
context["title"] = post.title(lang)
context["description"] = post.description(lang)
context["permalink"] = post.permalink(lang)
context["page_list"] = self.pages
output_name = os.path.join(
self.config["OUTPUT_FOLDER"],
self.config["TRANSLATIONS"][lang],
destination,
post.pagenames[lang] + ".html",
)
deps_dict = copy(context)
deps_dict.pop("post")
if post.prev_post:
deps_dict["PREV_LINK"] = [post.prev_post.permalink(lang)]
if post.next_post:
deps_dict["NEXT_LINK"] = [post.next_post.permalink(lang)]
deps_dict["OUTPUT_FOLDER"] = self.config["OUTPUT_FOLDER"]
deps_dict["TRANSLATIONS"] = self.config["TRANSLATIONS"]
task = {
"name": output_name.encode("utf-8"),
"file_dep": deps,
"targets": [output_name],
"actions": [(self.render_template, [template_name, output_name, context])],
"clean": True,
"uptodate": [config_changed(deps_dict)],
}
yield utils.apply_filters(task, filters)
def apply_actions_on_image(session_id, action_stack, filename,
image_signature):
action_stack = deepcopy(action_stack)
# If we have arrived to the original image
if len(action_stack) == 0 and LOCAL:
with open("image_string.csv", mode="r") as image_file:
image_reader = csv.DictReader(image_file)
for row in image_reader:
im_pil = drc.b64_to_pil(row["image"])
return im_pil
if len(action_stack) == 0 and not LOCAL:
# Retrieve the url in which the image string is stored inside s3,
# using the session ID
url = s3.generate_presigned_url(ClientMethod="get_object",
Params={
"Bucket": bucket_name,
"Key": session_id
})
# A key replacement is required for URL pre-sign in gcp
url = url.replace("AWSAccessKeyId", "GoogleAccessId")
response = requests.get(url)
if DEBUG:
print("IMAGE STRING LENGTH: " + str(len(response.text)))
im_pil = drc.b64_to_pil(response.text)
return im_pil
# Pop out the last action
last_action = action_stack.pop()
# Apply all the previous action_stack recursively, and gets the image PIL
im_pil = apply_actions_on_image(session_id, action_stack, filename,
image_signature)
im_size = im_pil.size
# Apply the rest of the action_stack
operation = last_action["operation"]
selected_data = last_action["selectedData"]
action_type = last_action["type"]
# Select using Lasso
if selected_data and "lassoPoints" in selected_data:
selection_mode = "lasso"
selection_zone = utils.generate_lasso_mask(im_pil, selected_data)
# Select using rectangular box
elif selected_data and "range" in selected_data:
selection_mode = "select"
lower, upper = map(int, selected_data["range"]["y"])
left, right = map(int, selected_data["range"]["x"])
# Adjust height difference
height = im_size[1]
upper = height - upper
lower = height - lower
selection_zone = (left, upper, right, lower)
# Select the whole image
else:
selection_mode = "select"
selection_zone = (0, 0) + im_size
# Apply the filters
if action_type == "filter":
utils.apply_filters(image=im_pil,
zone=selection_zone,
filter=operation,
mode=selection_mode)
elif action_type == "enhance":
enhancement = operation["enhancement"]
factor = operation["enhancement_factor"]
utils.apply_enhancements(
image=im_pil,
zone=selection_zone,
enhancement=enhancement,
enhancement_factor=factor,
mode=selection_mode,
)
return im_pil
def apply_actions_on_image(session_id,
action_stack,
filename,
image_signature):
action_stack = deepcopy(action_stack)
# If we have arrived to the original image
if len(action_stack) == 0:
# Retrieve the url in which the image string is stored inside s3,
# using the session ID
url = s3.generate_presigned_url(
ClientMethod='get_object',
Params={
'Bucket': bucket_name,
'Key': session_id
}
)
# A key replacement is required for URL pre-sign in gcp
url = url.replace('AWSAccessKeyId', 'GoogleAccessId')
response = requests.get(url)
print(len(response.text))
im_pil = drc.b64_to_pil(response.text)
return im_pil
# Pop out the last action
last_action = action_stack.pop()
# Apply all the previous action_stack, and gets the image PIL
im_pil = apply_actions_on_image(
session_id,
action_stack,
filename,
image_signature
)
im_size = im_pil.size
# Apply the rest of the action_stack
operation = last_action['operation']
selectedData = last_action['selectedData']
type = last_action['type']
# Select using Lasso
if selectedData and 'lassoPoints' in selectedData:
selection_mode = 'lasso'
selection_zone = generate_lasso_mask(im_pil, selectedData)
# Select using rectangular box
elif selectedData and 'range' in selectedData:
selection_mode = 'select'
lower, upper = map(int, selectedData['range']['y'])
left, right = map(int, selectedData['range']['x'])
# Adjust height difference
height = im_size[1]
upper = height - upper
lower = height - lower
selection_zone = (left, upper, right, lower)
# Select the whole image
else:
selection_mode = 'select'
selection_zone = (0, 0) + im_size
# Apply the filters
if type == 'filter':
apply_filters(
image=im_pil,
zone=selection_zone,
filter=operation,
mode=selection_mode
)
elif type == 'enhance':
enhancement = operation['enhancement']
factor = operation['enhancement_factor']
apply_enhancements(
image=im_pil,
zone=selection_zone,
enhancement=enhancement,
enhancement_factor=factor,
mode=selection_mode
)
return im_pil
def apply_actions_on_image(session_id, action_stack, filename,
image_signature):
action_stack = deepcopy(action_stack)
# If we have arrived to the original image
if len(action_stack) == 0 and LOCAL:
with open("image_string.csv", mode="r") as image_file:
image_reader = csv.DictReader(image_file)
for row in image_reader:
im_pil = drc.b64_to_pil(row["image"])
return im_pil
if len(action_stack) == 0 and not LOCAL:
pass
# Pop out the last action
last_action = action_stack.pop()
# Apply all the previous action_stack recursively, and gets the image PIL
im_pil = apply_actions_on_image(session_id, action_stack, filename,
image_signature)
im_size = im_pil.size
# Apply the rest of the action_stack
operation = last_action["operation"]
selected_data = last_action["selectedData"]
action_type = last_action["type"]
# Select using Lasso
if selected_data and "lassoPoints" in selected_data:
selection_mode = "lasso"
selection_zone = utils.generate_lasso_mask(im_pil, selected_data)
# Select using rectangular box
elif selected_data and "range" in selected_data:
selection_mode = "select"
lower, upper = map(int, selected_data["range"]["y"])
left, right = map(int, selected_data["range"]["x"])
# Adjust height difference
height = im_size[1]
upper = height - upper
lower = height - lower
selection_zone = (left, upper, right, lower)
# Select the whole image
else:
selection_mode = "select"
selection_zone = (0, 0) + im_size
# Apply the filters
if action_type == "filter":
utils.apply_filters(image=im_pil,
zone=selection_zone,
filter=operation,
mode=selection_mode)
elif action_type == "enhance":
enhancement = operation["enhancement"]
factor = operation["enhancement_factor"]
utils.apply_enhancements(
image=im_pil,
zone=selection_zone,
enhancement=enhancement,
enhancement_factor=factor,
mode=selection_mode,
)
return im_pil
def update_graph_interactive_image(content, n_clicks, figure, selectedData,
filters, enhance, enhancement_factor,
new_filename, dragmode, enc_format,
storage):
t1 = time.time()
# Retrieve metadata stored in the storage
filename = storage
# If the file has changed (when a file is uploaded)
if new_filename and new_filename != filename:
if DEBUG:
print(filename, "replaced by", new_filename)
string = content.split(';base64,')[-1]
im_pil = drc.b64_to_pil(string)
# If the file HAS NOT changed (which means an operation was applied)
else:
# Retrieve the image stored inside the figure
enc_str = figure['layout']['images'][0]['source'].split(';base64,')[-1]
# Creates the PIL Image object from the b64 png encoding
im_pil = drc.b64_to_pil(string=enc_str)
im_size = im_pil.size
# Select using Lasso
if selectedData and 'lassoPoints' in selectedData:
selection_mode = 'lasso'
selection_zone = generate_lasso_mask(im_pil, selectedData)
# Select using rectangular box
elif selectedData and 'range' in selectedData:
selection_mode = 'select'
lower, upper = map(int, selectedData['range']['y'])
left, right = map(int, selectedData['range']['x'])
# Adjust height difference
height = im_size[1]
upper = height - upper
lower = height - lower
selection_zone = (left, upper, right, lower)
# Select the whole image
else:
selection_mode = 'select'
selection_zone = (0, 0) + im_size
# If the filter dropdown was chosen, apply the filter selected by the user
if filters:
apply_filters(image=im_pil,
zone=selection_zone,
filter=filters,
mode=selection_mode)
if enhance:
apply_enhancements(image=im_pil,
zone=selection_zone,
enhancement=enhance,
enhancement_factor=enhancement_factor,
mode=selection_mode)
t2 = time.time()
if DEBUG:
print(f"Updated Image Storage in {t2-t1:.3f} sec")
return [
drc.InteractiveImagePIL(image_id='interactive-image',
image=im_pil,
enc_format=enc_format,
display_mode='fixed',
dragmode=dragmode,
verbose=DEBUG),
html.Div(id='div-filename-image',
children=new_filename,
style={'display': 'none'})
]
st.title("Film Recommender System")
cast_options, director_options, genres_options = get_filter_values(
filtered_films)
cast_default, director_default, genres_default = get_filter_values(data)
cast_filter, director_filter, genre_filter = st.columns(3)
cast = cast_filter.multiselect("Filter by cast", cast_options)
director = director_filter.multiselect("Filter by director", director_options)
genres = genre_filter.multiselect("Filter by genre", genres_options)
cast = cast_default if not cast else cast
director = director_default if not director else director
genres = genres_default if not genres else genres
if option == "Top Films":
filtered_films = apply_filters(data=data,
cast=cast,
director=director,
genres=genres,
sort_column="imdb_score")
filtered_films = filtered_films.loc[
filtered_films["vote_count"] >= config.m]
display_film_posters(
streamlit=st,
data=filtered_films,
num_rows=config.NUM_POSTER_ROWS,
posters_per_row=config.POSTERS_PER_ROW,
)
elif option == "Personal Recommendations":
if len(liked_films) == 0:
st.sidebar.write(
"Please select at least one film for recommendations.")
