def get_emotion():
file_name = request.args.get("file_name")
file_path = f"{base_path}{file_name}"
while not os.path.exists(file_path):
time.sleep(1)
if os.path.isfile(file_path):
d = dict()
responses = da_client.IdentifyEmotion(
chunk_generator_from_file(file_path), 2000, metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
d[response.emotion] = d.get(response.emotion, 0) + 1
print("Received message\n", response)
d = Counter(d)
word, _ = d.most_common(1)[0]
print(f"most common sentiment: {word.lower()}")
return word.lower()
else:
print(f"{file_path} isn't a file!")
return "error"
def get_tone_emotion():
responses = client.IdentifyEmotion(
# Use chunk_generator_from_file generator to stream from local file
chunk_generator_from_file(file_path),
# Use chunk_generator_from_url generator to stream from remote url or youtube with is_youtube_url set to true
# chunk_generator_from_url(file_path, is_youtube_url=is_youtube_url),
TIMEOUT_SECONDS, metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
#print("Received message",response)
emotion = str(response)
break
#print(type(x))
print(emotion)
# DeepAffects realtime Api client
client = get_deepaffects_client()
# chunk_generator() is a generator function which yields audio segment object asynchronously
metadata = [('apikey', apikey), ('speakerids', speakerIds),
('encoding', encoding), ('samplerate', sampleRate),
('languagecode', languageCode), ('apiversion', apiVersion),
('verbose', verbose)]
"""Stream audio from url or youtube.
responses = client.IdentifySpeaker(
chunk_generator_from_url(file_path, is_youtube_url=is_youtube_url), TIMEOUT_SECONDS, metadata=metadata)
"""
"""Stream audio from local file.
"""
responses = client.IdentifySpeaker(chunk_generator_from_file(file_path),
TIMEOUT_SECONDS,
metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
print("Received message")
print(response)
"""Response.
response = {
userId: userId of the speaker identified in the segment,
start: start of the segment,
end: end of the segment
}
"""
content: base64 encoded audio,
segmentOffset: offset of the segment in complete audio stream
"""
"""
Sample implementation which reads audio from a file and splits it into
segments more than 3 sec
AudioSegment and yields base64 encoded audio segment objects asynchronously
"""
"""Stream audio from url or youtube.
responses = client.IdentifyEmotion(
chunk_generator_from_url(file_path, is_youtube_url=is_youtube_url), TIMEOUT_SECONDS, metadata=metadata)
"""
"""Stream audio from local file.
"""
responses = client.IdentifyEmotion(chunk_generator_from_file(file_path),
TIMEOUT_SECONDS,
metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
print("Received message")
print(response)
"""Response.
response = {
emotion: Emotion identified in the segment,
start: start of the segment,
end: end of the segment
}
"""
content: base64 encoded audio,
segmentOffset: offset of the segment in complete audio stream
"""
"""
Sample implementation which reads audio from a file and splits it into
segments more than 3 sec
AudioSegment and yields base64 encoded audio segment objects asynchronously
"""
"""Stream audio from url or youtube.
responses = client.DiarizeEmotion(
chunk_generator_from_url(file_path, is_youtube_url=is_youtube_url), TIMEOUT_SECONDS, metadata=metadata)
"""
"""Stream audio from local file.
"""
responses = client.DiarizeEmotion(chunk_generator_from_file(file_path),
TIMEOUT_SECONDS,
metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
print("Received message")
print(response)
"""Response.
response = {
userId: userId of the speaker identified in the segment,
emotion: Emotion identified in the segment,
start: start of the segment,
end: end of the segment
}
"""
# segment_chunk(Args)
"""segment_chunk.
Args:
encoding : Audio Encoding,
languageCode: language code ,
sampleRate: sample rate of audio ,
content: base64 encoded audio,
segmentOffset: offset of the segment in complete audio stream
"""
# Call client api function with generator and metadata
responses = client.IdentifyEmotion(
# Use chunk_generator_from_file generator to stream from local file
chunk_generator_from_file(file_path),
# Use chunk_generator_from_url generator to stream from remote url or youtube with is_youtube_url set to true
# chunk_generator_from_url(file_path, is_youtube_url=is_youtube_url),
TIMEOUT_SECONDS,
metadata=metadata)
# responses is the iterator for all the response values
for response in responses:
print("Received message", response)
break
"""Response.
response = {
emotion: Emotion identified in the segment,
start: start of the segment,
end: end of the segment
}