/
image_search.py
118 lines (100 loc) · 3.41 KB
/
image_search.py
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# ---
# jupyter:
# jupytext:
# cell_metadata_filter: -all
# formats: ipynb,py
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.3.2
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# Image search
# ==============================
#
# ## Find studies and terms relevant to a brain map
import tempfile
import pathlib
from nilearn import image
from nilearn.plotting import view_img
import requests
from neuroquery_image_search import (
NeuroQueryImageSearch,
studies_to_html_table,
terms_to_html_table,
)
import ipywidgets as widgets
from IPython.display import display, display_html
# %%capture
search = NeuroQueryImageSearch()
uploader = widgets.FileUpload(accept="", multiple=False)
uploaded_button = widgets.Button(description="Search")
upload_info = widgets.HTML("Upload a .nii.gz image: ")
display(widgets.Box([upload_info, widgets.HBox([uploader, uploaded_button])]))
url_field = widgets.Text(
value="https://neurovault.org/media/images/4563/auditory.nii.gz"
)
url_button = widgets.Button(description="Search")
url_info = widgets.HTML("Or paste a URL: ")
display(widgets.Box([url_info, widgets.HBox([url_field, url_button])]))
output = widgets.Output()
display(output)
def search_and_display_img(img_factory):
try:
img, img_name = img_factory()
except Exception:
with output:
output.clear_output()
display_html(
"sorry, there was a problem with your image."
"please upload a .nii.gz 3D image",
raw=True,
)
else:
results = search(img, n_terms=12)
terms_table = terms_to_html_table(results["terms"])
studies_table = studies_to_html_table(results["studies"])
with output:
output.clear_output()
display_html("<h3>{}</h3>".format(img_name), raw=True)
display_html(
view_img(results["image"], threshold="95%").get_iframe(),
raw=True,
)
display_html(f"<h3>Similar terms:</h3>\n{terms_table}", raw=True)
display_html(
f"<h3>Similar studies:</h3>\n{studies_table}", raw=True
)
def _get_uploaded_img():
uploaded, *_ = uploader.value.values()
file_name, *_ = uploader.value.keys()
with tempfile.TemporaryDirectory() as tmp_dir:
image_path = str(pathlib.Path(tmp_dir) / "image.nii.gz")
with open(image_path, "wb") as f:
f.write(uploaded["content"])
img = image.load_img(image_path)
return img, file_name
def search_and_display_uploaded_img(_):
if not uploader.value:
with output:
output.clear_output()
display_html("please upload a .nii.gz 3D image", raw=True)
return
return search_and_display_img(_get_uploaded_img)
def _get_img_from_url():
url = url_field.value
resp = requests.get(url)
with tempfile.TemporaryDirectory() as tmp_dir:
image_path = str(pathlib.Path(tmp_dir) / "image.nii.gz")
with open(image_path, "wb") as f:
f.write(resp.content)
img = image.load_img(image_path)
return img, url
def search_and_display_img_from_url(_):
return search_and_display_img(_get_img_from_url)
uploaded_button.on_click(search_and_display_uploaded_img)
url_button.on_click(search_and_display_img_from_url)