def add_to_ranking_list():
playerid = request.args.get('playerid')
listid = request.args.get('listid')
player = Player.query.get(playerid)
if not player:
flash('Pelaajaa tunnuksella %s ei ole olemassa.' % playerid)
return redirect(utils.get_next_url())
if listid:
rlist = RankingList.query.get(listid)
ranking = Ranking(player, rlist)
db.session().add(ranking)
db.session.commit()
rankingrecord = RankingRecord(ranking)
db.session().add(rankingrecord)
db.session().commit()
flash('Pelaaja %s onnistuneesti lisätty listalle %s' %
(playerid, listid))
return redirect(utils.get_next_url())
player = Player.query.get(playerid)
lists = RankingList.get_suitable_ranking_lists(player)
return render_template('players/add_player_to_ranking_list.html',
data=[player],
lists=lists)
def train_post():
dataset_name = request.form["path"]
epochs = request.form["epochs"]
batch_size = request.form["batch_size"]
early_stopping = request.form.get("early_stopping") is not None
metadata_path = os.path.join(paths["datasets"], dataset_name,
METADATA_FILE)
audio_folder = os.path.join(paths["datasets"], dataset_name, AUDIO_FOLDER)
checkpoint_folder = os.path.join(paths["models"], dataset_name)
pretrained_folder = os.path.join(paths["pretrained"], dataset_name)
if request.files.get("pretrained_model"):
os.makedirs(pretrained_folder, exist_ok=True)
transfer_learning_path = os.path.join(pretrained_folder,
"pretrained.pt")
request.files["pretrained_model"].save(transfer_learning_path)
else:
transfer_learning_path = None
start_progress_thread(
train,
metadata_path=metadata_path,
dataset_directory=audio_folder,
output_directory=checkpoint_folder,
transfer_learning_path=transfer_learning_path,
epochs=int(epochs),
batch_size=int(batch_size),
early_stopping=early_stopping,
)
return render_template("progress.html",
next_url=get_next_url(URLS, request.path))
def create_dataset_post():
min_confidence = request.form["confidence"]
if request.form["name"]:
output_folder = os.path.join(paths["datasets"], request.form["name"])
if os.path.exists(output_folder):
request.files = None
raise Exception("Dataset name taken")
os.makedirs(output_folder, exist_ok=True)
text_path = os.path.join(output_folder, TEXT_FILE)
audio_path = os.path.join(output_folder, AUDIO_FILE)
forced_alignment_path = os.path.join(output_folder, ALIGNMENT_FILE)
output_path = os.path.join(output_folder, AUDIO_FOLDER)
label_path = os.path.join(output_folder, METADATA_FILE)
info_path = os.path.join(output_folder, INFO_FILE)
request.files["text_file"].save(text_path)
request.files["audio_file"].save(audio_path)
start_progress_thread(
create_dataset,
text_path=text_path,
audio_path=audio_path,
forced_alignment_path=forced_alignment_path,
output_path=output_path,
label_path=label_path,
info_path=info_path,
min_confidence=float(min_confidence),
)
else:
output_folder = os.path.join(paths["datasets"], request.form["path"])
suffix = get_suffix()
text_path = os.path.join(output_folder, f"text-{suffix}.txt")
audio_path = os.path.join(output_folder, f"audio-{suffix}.mp3")
forced_alignment_path = os.path.join(output_folder,
f"align-{suffix}.json")
info_path = os.path.join(output_folder, INFO_FILE)
request.files["text_file"].save(text_path)
request.files["audio_file"].save(audio_path)
existing_output_path = os.path.join(output_folder, AUDIO_FOLDER)
existing_label_path = os.path.join(output_folder, METADATA_FILE)
start_progress_thread(
extend_existing_dataset,
text_path=text_path,
audio_path=audio_path,
forced_alignment_path=forced_alignment_path,
output_path=existing_output_path,
label_path=existing_label_path,
suffix=suffix,
info_path=info_path,
min_confidence=float(min_confidence),
)
return render_template("progress.html",
next_url=get_next_url(URLS, request.path))
def get_list_info(ranking_list_id):
rlist = RankingList.query.get(ranking_list_id)
if not rlist:
flash('Listaa tunnuksella %s ei ole olemassa' % ranking_list_id)
return redirect(utils.get_next_url())
rlist.populate_players()
return render_template('rankings/ranking_list_info.html', data=[rlist])
def register():
form = RegisterForm(request.form)
if form.validate_on_submit():
user = User(form.name.data, form.username.data, form.role.data,
form.password.data)
db.session().add(user)
db.session().commit()
flash(u'Onnistuneesti rekisteröitynyt käyttäjä: %s' % user.username)
return redirect(utils.get_next_url())
return render_template('auth/register.html', form=form)
def train_post():
language = request.form["language"]
symbols = get_symbols(language)
dataset_name = request.form["dataset"]
epochs = request.form["epochs"]
batch_size = request.form["batch_size"]
early_stopping = request.form.get("early_stopping") is not None
iters_per_checkpoint = request.form["checkpoint_frequency"]
iters_per_backup_checkpoint = request.form["backup_checkpoint_frequency"]
train_size = 1 - float(request.form["validation_size"])
alignment_sentence = request.form["alignment_sentence"]
multi_gpu = request.form.get("multi_gpu") is not None
checkpoint_path = (os.path.join(paths["models"], dataset_name,
request.form["checkpoint"])
if request.form.get("checkpoint") else None)
metadata_path = os.path.join(paths["datasets"], dataset_name,
METADATA_FILE)
use_metadata = os.path.isfile(metadata_path)
trainlist_path = os.path.join(paths["datasets"], dataset_name, TRAIN_FILE)
vallist_path = os.path.join(paths["datasets"], dataset_name,
VALIDATION_FILE)
audio_folder = os.path.join(paths["datasets"], dataset_name, AUDIO_FOLDER)
checkpoint_folder = os.path.join(paths["models"], dataset_name)
if request.files.get("pretrained_model"):
transfer_learning_path = os.path.join("data", "pretrained.pt")
request.files["pretrained_model"].save(transfer_learning_path)
else:
transfer_learning_path = None
start_progress_thread(
train,
metadata_path=metadata_path if use_metadata else None,
trainlist_path=trainlist_path if not use_metadata else None,
vallist_path=vallist_path if not use_metadata else None,
audio_directory=audio_folder,
output_directory=checkpoint_folder,
symbols=symbols,
checkpoint_path=checkpoint_path,
transfer_learning_path=transfer_learning_path,
epochs=int(epochs),
batch_size=int(batch_size),
early_stopping=early_stopping,
multi_gpu=multi_gpu,
iters_per_checkpoint=int(iters_per_checkpoint),
iters_per_backup_checkpoint=int(iters_per_backup_checkpoint),
train_size=train_size,
alignment_sentence=alignment_sentence,
)
return render_template("progress.html",
next_url=get_next_url(URLS, request.path),
voice=Path(checkpoint_folder).stem)
def get_player_info(playerid):
player_data = Player.query.get(playerid)
if player_data:
rlists = RankingList.query.filter(
RankingList.id.in_([
r.list_id
for r in Ranking.query.filter_by(player_id=player_data.id)
]))
return render_template('players/player_info.html',
data=[player_data],
rlists=rlists)
else:
flash('Pelaajaa tunnuksella %s ei ole olemassa.' % playerid)
return redirect(utils.get_next_url())
def retire_player(playerid):
player_data = Player.query.get(playerid)
if not player_data:
flash('Pelaajaa tunnuksella %s ei ole olemassa.' % playerid)
return redirect(utils.get_next_url())
rankings = Ranking.query.filter_by(player_id=player_data.id).all()
for ranking in rankings:
RankingRecord.query.filter_by(ranking_id=ranking.id).delete()
Ranking.query.filter_by(player_id=player_data.id).delete()
db.session().delete(player_data)
db.session.commit()
flash('Onnistuneesti poistettiin pelaaja %s.' % player_data.name)
return redirect(url_for('index'))
def edit_player(playerid):
player = Player.query.get(playerid)
if not player:
flash('Pelaajaa tunnuksella %s ei ole olemassa.' % playerid)
return redirect(utils.get_next_url())
form = PlayerForm(player=player)
if form.validate_on_submit():
player = db.session.query(Player).get(playerid)
player.name = form.name.data
player.gender = form.gender.data
player.dateofbirth = form.dob.data
player.placeofbirth = form.pob.data
db.session.commit()
flash('Onnistuneesti muokattiin pelaajaa %s' % playerid)
return render_template('players/player_info.html', data=[player])
return render_template('players/edit_player.html', form=form)
def create_dataset_post():
min_confidence = float(request.form["confidence"])
language = request.form["language"]
combine_clips = request.form.get("combine_clips") is not None
min_length = float(request.form["min_length"])
max_length = float(request.form["max_length"])
transcription_model = (
Silero(language) if language in SILERO_LANGUAGES else DeepSpeech(
os.path.join(paths["languages"], language, TRANSCRIPTION_MODEL)))
symbols = get_symbols(language)
text_file = SUBTITLE_FILE if request.files["text_file"].filename.endswith(
".srt") else TEXT_FILE
if request.form["name"]:
output_folder = os.path.join(paths["datasets"], request.form["name"])
if os.path.exists(output_folder):
request.files = None
raise Exception("Dataset name taken")
os.makedirs(output_folder, exist_ok=True)
text_path = os.path.join(output_folder, text_file)
audio_path = os.path.join(output_folder,
request.files["audio_file"].filename)
with open(text_path, "w", encoding=CHARACTER_ENCODING) as f:
f.write(request.files["text_file"].read().decode(
CHARACTER_ENCODING, "ignore").replace("\r\n", "\n"))
request.files["audio_file"].save(audio_path)
start_progress_thread(
create_dataset,
text_path=text_path,
audio_path=audio_path,
transcription_model=transcription_model,
output_folder=output_folder,
min_length=min_length,
max_length=max_length,
min_confidence=min_confidence,
combine_clips=combine_clips,
symbols=symbols,
)
else:
output_folder = os.path.join(paths["datasets"],
request.form["dataset"])
suffix = get_suffix()
text_path = os.path.join(output_folder, add_suffix(text_file, suffix))
audio_path = os.path.join(
output_folder,
add_suffix(request.files["audio_file"].filename, suffix))
with open(text_path, "w", encoding=CHARACTER_ENCODING) as f:
f.write(request.files["text_file"].read().decode(
CHARACTER_ENCODING, "ignore").replace("\r\n", "\n"))
request.files["audio_file"].save(audio_path)
start_progress_thread(
extend_existing_dataset,
text_path=text_path,
audio_path=audio_path,
transcription_model=transcription_model,
output_folder=output_folder,
suffix=suffix,
min_length=min_length,
max_length=max_length,
min_confidence=min_confidence,
combine_clips=combine_clips,
symbols=symbols,
)
return render_template("progress.html",
next_url=get_next_url(URLS, request.path))