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#!/usr/bin/env python
"""Magni."""
import argparse
import concurrent.futures
import http.server
import os
import socketserver
import typing
import bs4
import cv2 # type:ignore
import requests
class Argparser: # pylint: disable=too-few-public-methods
"""Argparser class."""
def __init__(self):
self.parser = argparse.ArgumentParser()
self.parser.add_argument(
"--url",
"-u",
type=str,
help="the url to the page containing the images",
default=False,
)
self.parser.add_argument(
"--port",
"-p",
type=int,
help="the port to serve the images over",
default=6666,
)
self.args = self.parser.parse_args()
def get_model_path() -> str:
"""Get the model path."""
# FIXME- add path if it doesnt exist
if "MAGNI_MODEL_PATH" in os.environ and os.environ["MAGNI_MODEL_PATH"]:
return os.environ["MAGNI_MODEL_PATH"]
return "./models"
def get_image_path() -> str:
"""Get the image path."""
# FIXME- add path if it doesnt exist
if "MAGNI_IMAGE_PATH" in os.environ and os.environ["MAGNI_IMAGE_PATH"]:
return os.environ["MAGNI_IMAGE_PATH"]
return "./images"
def espcn_superscaler(img):
"""ESPCN superscaler."""
superres = cv2.dnn_superres.DnnSuperResImpl_create()
path = get_model_path() + "/" + "ESPCN_x3.pb"
superres.readModel(path)
superres.setModel("espcn", 3)
result = superres.upsample(img)
return result
def fsrcnn_superscaler(img):
"""FSRCNN superscaler"""
superres = cv2.dnn_superres.DnnSuperResImpl_create()
path = get_model_path() + "/" + "FSRCNN_x3.pb"
superres.readModel(path)
superres.setModel("fsrcnn", 3)
result = superres.upsample(img)
return result
def get_proxies() -> typing.Dict:
"""Get the proxy env vars."""
http_proxy: typing.Optional[str] = None
if "HTTP_PROXY" in os.environ and os.environ["HTTP_PROXY"] != "":
http_proxy = os.environ["HTTP_PROXY"]
https_proxy: typing.Optional[str] = None
if "HTTPS_PROXY" in os.environ and os.environ["HTTPS_PROXY"] != "":
https_proxy = os.environ["HTTPS_PROXY"]
no_proxy: typing.Optional[str] = None
if "NO_PROXY" in os.environ and os.environ["NO_PROXY"] != "":
no_proxy = os.environ["NO_PROXY"]
return {"http": http_proxy, "https": https_proxy, "no_proxy": no_proxy}
def single_get(url: str) -> requests.Response:
"""A simple get."""
return requests.get(
url, allow_redirects=True, timeout=10, proxies=get_proxies()
)
def multi_get(urls: list) -> list:
"""Async get."""
with concurrent.futures.ThreadPoolExecutor(max_workers=16) as pool:
response_list = list(pool.map(single_get, urls))
return response_list
def single_get_tag(url_tag_pair: list) -> typing.Tuple[requests.Response, str]:
"""A simple get with a tag."""
return (
requests.get(
url_tag_pair[0],
allow_redirects=True,
timeout=10,
proxies=get_proxies(),
),
url_tag_pair[1],
)
def multi_get_tag(
urls: typing.List[typing.Tuple[str, str]],
) -> typing.Optional[typing.List[typing.Tuple[requests.Response, str]]]:
"""Async get with a tag."""
with concurrent.futures.ThreadPoolExecutor(max_workers=16) as pool:
response_list = list(pool.map(single_get_tag, urls))
return response_list
def model_downloader() -> None:
"""Download the models."""
down_list = [
"https://github.com/fannymonori/TF-ESPCN/raw/master/export/ESPCN_x3.pb",
"https://github.com/fannymonori/TF-ESPCN/raw/master/export/ESPCN_x2.pb",
"https://github.com/fannymonori/TF-ESPCN/raw/master/export/ESPCN_x4.pb",
"https://github.com/Saafke/FSRCNN_Tensorflow/raw/master/models/FSRCNN_x4.pb",
"https://github.com/Saafke/FSRCNN_Tensorflow/raw/master/models/FSRCNN_x3.pb",
"https://github.com/Saafke/FSRCNN_Tensorflow/raw/master/models/FSRCNN_x2.pb",
]
url_tag_list: typing.List[typing.Tuple[str, str]] = []
for url in down_list:
url_tag_list.append((url, url[url.rfind("/") + 1 :]))
response_list: typing.Optional[
typing.List[typing.Tuple[requests.Response, str]]
] = multi_get_tag(url_tag_list)
model_path: str = os.getcwd()
if (
"MAGNI_MODEL_PATH" in os.environ
and os.environ["MAGNI_MODEL_PATH"] != ""
):
model_path = os.environ["MAGNI_MODEL_PATH"]
if response_list is None:
return None
for response, name in response_list:
with open(model_path + "/" + name, mode="b+w") as downed:
downed.write(response.content)
return None
def download_all_images(url: str) -> None:
"""Sniffs images."""
response = requests.get(url, timeout=10, allow_redirects=True)
if response.content is None:
return None
soup = bs4.BeautifulSoup(response.content, "lxml")
search_results = soup.findAll("img")
image_url_list: typing.List[typing.Tuple[str, str]] = [
(result["src"], result["src"][result["src"].rfind("/") + 1 :])
for result in search_results
]
print(image_url_list)
response_list: typing.Optional[
typing.List[typing.Tuple[requests.Response, str]]
] = multi_get_tag(image_url_list)
print(response_list)
if response_list is None:
return None
for response, name in response_list:
with open(get_image_path() + "/" + name, "w+b") as image:
image.write(response.content)
return None
def serve(port_number: int) -> None:
"""Startup a simple http file server."""
handler = http.server.SimpleHTTPRequestHandler
with socketserver.TCPServer(("", port_number), handler) as httpd:
httpd.serve_forever()
def main() -> None:
"""Entry point."""
argparser = Argparser()
model_downloader()
download_all_images(argparser.args.url)
if __name__ == "__main__":
main()
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