In [ ]:
import os
from os.path import exists, join, basename, splitext, abspath
git_repo_url = 'https://github.com/ZJULearning/pixel_link.git'
project_name = splitext(basename(git_repo_url))[0]
if not exists(project_name):
# clone and install
!git clone -q $git_repo_url
# make opencv3 compatible
!sed -i 's/cv2.cv.BoxPoints/cv2.boxPoints/' $project_name/pixel_link.py
# save output to output.png
!sed -i 's/print util.sit(image_data)/print util.sit(image_data, format="bgr", path="\/content\/output.png")/' $project_name/test_pixel_link_on_any_image.py
# submodule doesn't work, checkout manually
!cd $project_name && rm -rf pylib && git clone -q https://github.com/dengdan/pylib.git && cd pylib && git checkout e749559
os.environ['PYTHONPATH'] += ':' + join(abspath(project_name), 'pylib/src')
#!cd $project_name && pip install -q -r requirements.txt
import sys
sys.path.append(project_name)
import time
import matplotlib
import matplotlib.pylab as plt
plt.rcParams["axes.grid"] = False
Download pretrained model¶
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def download_from_google_drive(file_id, file_name):
# download a file from the Google Drive link
!rm -f ./cookie
!curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=$file_id" > /dev/null
confirm_text = !awk '/download/ {print $NF}' ./cookie
confirm_text = confirm_text[0]
!curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=$confirm_text&id=$file_id" -o $file_name
pretrained_model = 'conv3_3'
if not exists(pretrained_model):
# download the pretrained model
pretrained_model_file_name = 'pixel_link_vgg_4s.zip'
download_from_google_drive('19mlX5W8OBalSjhf5oTTS6qEq2eAU8Tg9', pretrained_model_file_name)
!unzip $pretrained_model_file_name
Detect scene text on a test image¶
First, dowload a test image from internet:
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IMAGE_URL = 'https://raw.githubusercontent.com/tugstugi/dl-colab-notebooks/master/resources/billboard.jpg'
image_file_name = basename(IMAGE_URL)
download_dir = '/content/images'
!mkdir -p $download_dir && rm -rf $download_dir/*
!wget -q -P $download_dir $IMAGE_URL
plt.imshow(matplotlib.image.imread(join(download_dir, image_file_name)))
Out[ ]:
<matplotlib.image.AxesImage at 0x7f1cc1876850>
Run PixelLink on the above test image:
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!cd $project_name && ./scripts/test_any.sh 0 ../conv3_3/model.ckpt-38055 $download_dir
Now, visualize the result:
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plt.figure(figsize=(20, 26))
plt.imshow(matplotlib.image.imread('output.png'))
Out[ ]:
<matplotlib.image.AxesImage at 0x7f1cbf6e5c10>
