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import express, {Request, Response} from "express"; | |
import Anthropic from "@anthropic-ai/sdk"; | |
import cors from "cors"; | |
import { exec, ExecException } from 'child_process'; | |
import { readFile, writeFile, readdir} from 'fs/promises'; | |
import { OpenAI } from "openai"; | |
import { json, urlencoded } from "body-parser"; | |
import * as http from "http"; | |
import getCategoryName from './imagenetLabels'; |
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003bb1cf-143d-42d4-b760-b98b96d0db5c.mkv | |
0043001d-0c08-40eb-8543-21010804eb0b.mkv | |
0048f2de-d154-46d8-a46d-0bf4ea021e1a.mkv | |
0051fc71-751c-4a3f-90fe-7d677792a759.mkv | |
0053d44a-f63a-44e8-9c3b-a23033d67557.mkv | |
0064e7ea-804e-4167-951c-70454ee20515.mkv | |
0065f790-264f-4d05-9a37-de27c24946cf.mkv | |
0069cf46-da33-46b7-a205-6716ab92a327.mkv | |
00796e0b-ed18-4cf2-bbc6-0e6c5394273f.mkv | |
007d6d94-682f-4ff6-b1fd-a1809d79a927.mkv |
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import UIKit | |
import AVFoundation | |
import SwiftUI | |
// Image Extraction | |
protocol FrameExtractorDelegate: class { |
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X | |
<figure> | |
<figcaption>Listen to the T-Rex:</figcaption> | |
<audio | |
controls | |
src="https://s3.ap-northeast-2.amazonaws.com/audio-streaming-test/2018-11-30+ %E1%84%86%E1%85%A6%E1%86%AB%E1%84%90%E1%85%A1%E1%86%AF%E1%84%80%E1%85%AE%E1%84%8C%E1%85%A9%E1%84%83%E1%85%A2+ 1%E1%84%87%E1%85%AE(%E1%84%90%E1%85%A9%E1%86%BC%E1%84%92%E1%85%A1%E1%86%B8).mp3"> | |
Your browser does not support the | |
<code>audio</code> element. | |
</audio> | |
figure> |
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{ | |
"audio": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ] | |
} |
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# python for loop | |
for d in Dataset: | |
d = preprocessing(d) | |
write_tfrecord(d) | |
# python map function | |
itr = map(preprocessing, Dataset) | |
for i in itr: | |
write_tfrecord(i) |
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import tensorflow as tf | |
def input_fn(): | |
dataset = tf.data.TFRecordDataset('dataset_path') | |
dataset = dataset.batch(10) | |
dataset = dataset.shuffle(6666) | |
dataset = dataset.repeat(10) |
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import csv | |
import os | |
hand_path = '/Users/chanwoo/Documents/sources/IEMOCAP_full_release/Session1/dialog/MOCAP_hand/' | |
label_path = '/Users/chanwoo/Documents/sources/IEMOCAP_full_release/Session1/dialog/EmoEvaluation/' | |
filename = 'Ses01F_impro01.txt' | |
with open(os.path.join(hand_path, filename), 'r') as f: | |
raw_text = f.read() |
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import tensorflow as tf | |
import numpy as np | |
import matplotlib.pyplot as plt | |
tf.reset_default_graph() | |
data = [[i for i in range(10)] for _ in range(1000)] | |
noise = np.random.randn(1000, 10) | |
real_data = tf.placeholder(tf.float32, shape=[None, 10]) |
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