Project Stage | Project Storyline | Hiking Analogy Storyline |
---|---|---|
Project Initiation | Started a machine vision and Gen-AI solution for an e-commerce company, expecting a straightforward implementation. | Embarked on a hike to a renowned Grenadian waterfall, expecting an easy journey based on initial guidance. |
Embarking on a journey to develop a machine vision and Gen-AI based solution for auto-tagging and recommending relat |
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from typing import Literal | |
import streamlit as st | |
from streamlit.components.v1 import html | |
FIXED_CONTAINER_CSS = """ | |
div[data-testid="stVerticalBlockBorderWrapper"]:has(div.fixed-container-{id}):not(:has(div.not-fixed-container)) {{ | |
position: {mode}; | |
width: inherit; |
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""" | |
a script in Python that given a directory path as input, converts all images in the directory to PDF files. Several other argswitches are available for convenience. | |
""" | |
import argparse | |
import logging | |
import os | |
import pprint as pp | |
import sys |
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""" | |
define fn for extracting articles | |
Example usage: | |
url = 'https://www.businessinsider.com/hundreds-google-workers-walk-out-zurich-protest-over-layoffs-2023-3' | |
markdown = extract_article(url) | |
print(markdown) | |
""" |
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# -*- coding: utf-8 -*- | |
""" | |
caption_image.py - basic captioning example using lavis | |
usage: caption_image.py [-h] -i IMAGE_PATH [-m MODEL_TYPE] [-d DEVICE] [-v VERBOSE] | |
# lavis | |
https://github.com/salesforce/LAVIS | |
""" |
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