f.write(s)
#%% Generate preview, sanity-check labels
from visualization import visualize_db
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 5000
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = True
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
viz_options.classes_to_exclude = ['test','empty']
# viz_options.classes_to_include = ['jackalblackbacked','bustardkori']
html_output_file, image_db = visualize_db.process_images(db_path=json_filename,
output_dir=output_preview_folder,
image_base_dir=output_public_folder,
options=viz_options)
os.startfile(html_output_file)
#%% Scrap
if False:
pass
#%% Find annotations for a particular image
fn = missing_images[1000]
id = fn.replace('.JPG','')
im = im_id_to_image[id]
#%% Preview labels
from visualization import visualize_db
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 100
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = False
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
viz_options.include_filename_links = True
# viz_options.classes_to_exclude = ['test']
html_output_file, _ = visualize_db.process_images(db_path=output_json,
output_dir=os.path.join(
base_folder,'preview'),
image_base_dir=os.path.join(base_folder,'images'),
options=viz_options)
os.startfile(html_output_file)
#%% ############ Take two, from pre-iWildCam .json files created from IDFG .csv files ############
#%% Imports and constants
import json
import os
base_folder = r'h:\idaho-camera-traps'
input_json_sl = os.path.join(base_folder,'iWildCam_IDFG.json')
input_json = os.path.join(base_folder,'iWildCam_IDFG_ml.json')
options = sanity_check_json_db.SanityCheckOptions()
options.baseDir = imageBaseDir
options.bCheckImageSizes = False
options.bFindUnusedImages = False
sanity_check_json_db.sanity_check_json_db(outputFile, options)
#%% Preview a few images to make sure labels were passed along sensibly
db_path = outputFile
output_dir = os.path.join(baseDir,'label_preview')
image_base_dir = imageBaseDir
options = visualize_db.DbVizOptions()
options.num_to_visualize = 100
htmlOutputFile = visualize_db.process_images(db_path,output_dir,image_base_dir,options)
#%% One-time processing step: copy images to a flat directory for annotation
if False:
#%%
from shutil import copyfile
os.makedirs(imageFlatDir,exist_ok=True)
for sourcePath in tqdm.tqdm(imageFullPaths):
fn = ntpath.basename(sourcePath)
targetPath = os.path.join(imageFlatDir,fn)
assert not os.path.isfile(targetPath)
sortedCategories, data = sanity_check_json_db.sanity_check_json_db(output_json_file,options)
#%% Preview labels
from visualization import visualize_db
from data_management.databases import sanity_check_json_db
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 1000
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = True
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
html_output_file,image_db = visualize_db.process_images(db_path=output_json_file,
output_dir=os.path.join(output_base,'preview'),
image_base_dir=image_directory,
options=viz_options)
os.startfile(html_output_file)
#%% Scrap
if False:
pass
#%% Find unique photo types
annotations = image_db['annotations']
photo_types = set()
for ann in tqdm(annotations):
print('Finished writing .json file with {} images, {} annotations, and {} categories'.format(
len(images),len(annotations),len(categories)))
#%% Validate output
fn = output_file
options = sanity_check_json_db.SanityCheckOptions()
options.baseDir = image_directory
options.bCheckImageSizes = False
options.bCheckImageExistence = True
options.bFindUnusedImages = True
sortedCategories, data = sanity_check_json_db.sanity_check_json_db(fn, options)
#%% Preview labels
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 1000
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = True
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
html_output_file, image_db = visualize_db.process_images(db_path=output_file,
output_dir='/home/gramener/previewB',
image_base_dir=image_directory,
options=viz_options)
os.startfile(html_output_file)
options.bCheckImageSizes = False
options.bCheckImageExistence = True
options.bFindUnusedImages = False
sortedCategories = sanity_check_json_db.sanity_check_json_db(
indexedData.db, options)
#%% Label previews
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 500
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = True
viz_options.sort_by_filename = False
html_output_file, image_db = visualize_db.process_images(
indexedData.db, os.path.join(output_base, 'preview'), image_base,
viz_options)
os.startfile(html_output_file)
#%% Collect images to annotate
images_to_annotate = []
annotation_list = set(annotation_list)
n_humans = 0
for im in tqdm(indexedData.db['images']):
class_names = indexedData.get_classes_for_image(im)
b_human = False
for cn in class_names:
_, _, _ = integrity_check_json_db.integrity_check_json_db(
output_json_filename, options)
#%% Preview labels
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 300
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = True
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
viz_options.include_filename_links = True
html_output_file, _ = visualize_db.process_images(db_path=output_json_filename,
output_dir=preview_base,
image_base_dir=image_base,
options=viz_options)
open_file(html_output_file)
# open_file(os.path.join(image_base,'2100703/1141a545-88d2-498b-a684-7431f7aeb324.jpg'))
#%%
if create_ordered_dataset:
pass
#%% Create ordered dataset
# Because WI filenames are GUIDs, it's not practical to page through sequences in an
# image viewer. So we're going to create a copy of the data set where images are
# ordered.
data['categories'] = categoriesSet2
json.dump(data, open(outputJsonFilenameSet2, 'w'), indent=4)
print('Finished writing json to {}'.format(outputJsonFilenameSet2))
#%% Sanity-check final set 1 .json file
from data_management.databases import sanity_check_json_db
options = sanity_check_json_db.SanityCheckOptions()
sortedCategories, data = sanity_check_json_db.sanity_check_json_db(
outputJsonFilenameSet1, options)
sortedCategories
# python sanity_check_json_db.py --bCheckImageSizes --baseDir "E:\wildlife_data\missouri_camera_traps" "E:\wildlife_data\missouri_camera_traps\missouri_camera_traps_set1.json"
#%% Generate previews
from visualization import visualize_db
output_dir = os.path.join(baseDir, 'preview')
options = visualize_db.DbVizOptions()
options.num_to_visualize = 1000
options.sort_by_filename = False
options.classes_to_exclude = None
htmlOutputFile, _ = visualize_db.process_images(outputJsonFilenameSet1,
output_dir, baseDir, options)
os.startfile(htmlOutputFile)
# Generate previewse:\wildlife_data\missouri_camera_traps\missouri_camera_traps_set1.json" "e:\wildlife_data\missouri_camera_traps\preview" "e:\wildlife_data\missouri_camera_traps" --num_to_visualize 1000
# im = images[0]
if n_threads == 1:
for im in tqdm(data['images']):
copy_image(im)
else:
pool = ThreadPool(n_threads)
with tqdm(total=len(data['images'])) as pbar:
for i, _ in enumerate(pool.imap_unordered(copy_image, data['images'])):
pbar.update()
#%% Preview labels
from visualization import visualize_db
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 100
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = False
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
viz_options.include_filename_links = True
# viz_options.classes_to_exclude = ['test']
html_output_file, _ = visualize_db.process_images(
db_path=output_json_filename,
output_dir=os.path.join(output_base, 'preview'),
image_base_dir=os.path.join(output_image_base, 'public'),
options=viz_options)
os.startfile(html_output_file)
print(
'Finished writing .json file with {} images, {} annotations, and {} categories'
.format(len(images), len(annotations), len(categories)))
#%% Sanity-check the database's integrity
json_data = json.load(open(output_file))
options = sanity_check_json_db.SanityCheckOptions()
sortedCategories, data = sanity_check_json_db.sanity_check_json_db(
json_data, options)
#%% Render a bunch of images to make sure the labels got carried along correctly
output_dir = preview_base
options = visualize_db.DbVizOptions()
options.num_to_visualize = 100
options.sort_by_filename = False
# options.classes_to_exclude = ['unlabeled']
options.classes_to_exclude = None
htmlOutputFile, _ = visualize_db.process_images(json_data, output_dir,
input_base, options)
os.startfile(htmlOutputFile)
#%% Write out a list of files to annotate
_, file_list = cct_json_to_filename_json.convertJsonToStringList(
output_file, prepend="20190715/")
os.startfile(file_list)
options.bCheckImageExistence = False
options.bFindUnusedImages = False
sorted_categories, data, errors = sanity_check_json_db.sanity_check_json_db(
fn, options)
#%% Preview animal labels
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 3000
viz_options.trim_to_images_with_bboxes = False
viz_options.add_search_links = False
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
html_output_file, image_db = visualize_db.process_images(
db_path=output_json_file,
output_dir=os.path.join(output_dir_base, 'preview_animals'),
image_base_dir=image_base_folder,
options=viz_options)
os.startfile(html_output_file)
#%% Preview empty labels
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 3000
viz_options.trim_to_images_with_bboxes = False
# viz_options.classes_to_exclude = ['empty','human']
viz_options.classes_to_include = ['empty']
viz_options.add_search_links = False
viz_options.sort_by_filename = False
viz_options.parallelize_rendering = True
html_output_file, image_db = visualize_db.process_images(
print('{} missing images in {} bounding boxes ({} found)'.format(
len(missing_images), len(bbox_data['annotations']), len(found_images)))
#%% Sanity-check a few files to make sure bounding boxes are still sensible
# import sys; sys.path.append(r'C:\git\CameraTraps')
from visualization import visualize_db
output_base = r'E:\snapshot_temp'
viz_options = visualize_db.DbVizOptions()
viz_options.num_to_visualize = 500
viz_options.trim_to_images_with_bboxes = True
viz_options.add_search_links = True
viz_options.sort_by_filename = False
html_output_file, bbox_db = visualize_db.process_images(
bbox_json_fn, os.path.join(output_base, 'preview2'), image_base,
viz_options)
os.startfile(html_output_file)
#%% Check categories
json_fn_all = r"E:\snapshot_out\SnapshotSeregeti_v2.0.json"
with open(json_fn_all, 'r') as f:
data_all = json.load(f)
data_by_season = []
data_10 = None
i_season = 9
fn = r'e:\snapshot_out\SnapshotSerengetiS{:0>2d}.json'.format(i_season + 1)
with open(fn, 'r') as f:
#%% Write output
json_data = {}
json_data['images'] = images
json_data['annotations'] = annotations
json_data['categories'] = categories
json_data['info'] = info
json.dump(json_data, open(output_file, 'w'), indent=1)
print(
'Finished writing .json file with {} images, {} annotations, and {} categories'
.format(len(images), len(annotations), len(categories)))
#%% Sanity-check the database's integrity
options = sanity_check_json_db.SanityCheckOptions()
sortedCategories, data = sanity_check_json_db.sanity_check_json_db(
output_file, options)
#%% Render a bunch of images to make sure the labels got carried along correctly
options = visualize_db.DbVizOptions()
options.num_to_visualize = 1000
options.parallelize_rendering = True
options.sort_by_filename = False
options.classes_to_exclude = ['unlabeled', 'empty', 'ambiguous']
html_output_file, data = visualize_db.process_images(output_file, preview_base,
file_base, options)
os.startfile(html_output_file)
