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# Setup: | |
# conda create -n whisper python=3.9 | |
# conda activate whisper | |
# https://github.com/openai/whisper | |
# pip install git+https://github.com/openai/whisper.git | |
# Usage: | |
# python whisper-audio-to-text.py --audio_dir my_files --out_dir texts | |
import argparse |
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class TransformerBlock(layers.Layer): | |
"""A generic Transformer block with MHSA and MLP layers. | |
Args: | |
config: The configuration of the architecture. | |
""" | |
def __init__(self, config, **kwargs): | |
super().__init__(**kwargs) | |
self.config = config | |
self.layer_norm1 = layers.LayerNormalization( |
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# This is the problem for First technical round for the role of Computer Vision Engineer at Vectorly | |
# More details at https://www.linkedin.com/jobs/view/1629909785/ | |
# | |
# Write a function which will segment and extract the text overlay "Bart & Homer's EXCELLENT Adventure" | |
# Input image is at https://vectorly.io/demo/simpsons_frame0.png | |
# Output : Image with only the overlay visible and everything else white | |
# | |
# Note that you don't need to extract the text, the output is an image with only | |
# the overlay visible and everything else (background) white | |
# |
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import matplotlib.pyplot as plt | |
import numpy as np | |
def show_images(images, cols = 1, titles = None): | |
"""Display a list of images in a single figure with matplotlib. | |
Parameters | |
--------- | |
images: List of np.arrays compatible with plt.imshow. | |