duplicate_finder.py

#!/usr/bin/env python3
"""
A tool to find and remove duplicate pictures.

Usage:
    duplicate_finder.py add <path> ... [--db=<db_path>] [--parallel=<num_processes>]
    duplicate_finder.py remove <path> ... [--db=<db_path>]
    duplicate_finder.py clear [--db=<db_path>]
    duplicate_finder.py show [--db=<db_path>]
    duplicate_finder.py cleanup [--db=<db_path>]
    duplicate_finder.py find [--print] [--delete] [--match-time] [--trash=<trash_path>] \
[--db=<db_path>] [--threshold=<num>]
    duplicate_finder.py -h | --help

Options:
    -h, --help                Show this screen

    --db=<db_path>            The location of the database or a MongoDB URI. (default: ./db)

    --parallel=<num_processes> The number of parallel processes to run to hash the files
                               (default: number of CPUs).

    find:
        --threshold=<num>     Hash matching threshold. Number of different bits in Hamming \
distance. False positives are possible.
        --print               Only print duplicate files rather than displaying HTML file
        --delete              Move all found duplicate files to the trash. This option \
takes priority over --print.
        --match-time          Adds the extra constraint that duplicate images must have the
                              same capture times in order to be considered.
        --trash=<trash_path>  Where files will be put when they are deleted (default: ./Trash)
"""

import concurrent.futures
from contextlib import contextmanager
import os
import math
from pprint import pprint
import shutil
from subprocess import Popen, PIPE, TimeoutExpired
import sys
from tempfile import TemporaryDirectory

import webbrowser
import binascii
import io
from jinja2 import FileSystemLoader, Environment
from flask import Flask, Response
from flask_cors import CORS


from more_itertools import chunked
import pymongo
from PIL import Image
import pybktree
from termcolor import cprint

from hashers import BinaryHasher, ImageHasher, VideoHasher  # , VideoBarcodeHasher
from utils import ProgressBarPrinter


def get_hashers() -> list:
    """Return array of active hashers"""
    return [
        BinaryHasher(),
        ImageHasher(),
        VideoHasher(ImageHasher()),
        # VideoBarcodeHasher(ImageHasher()),
    ]


@contextmanager
def connect_to_db(db_conn_string='./db'):
    """Connect to mongo"""
    p = None

    # Determine db_conn_string is a mongo URI or a path
    # If this is a URI
    if 'mongodb://' == db_conn_string[:10] \
            or 'mongodb+srv://' == db_conn_string[:14]:
        client = pymongo.MongoClient(db_conn_string)
        cprint("Connected server...", "yellow")
        db = client.image_database
        images = db.images

    # If this is not a URI
    else:
        if not os.path.isdir(db_conn_string):
            os.makedirs(db_conn_string)

        p = Popen(['mongod', '--dbpath', db_conn_string],
                  stdout=PIPE, stderr=PIPE)

        try:
            p.wait(timeout=2)
            stdout, _ = p.communicate()
            cprint("Error starting mongod", "red")
            cprint(stdout.decode(), "red")
            sys.exit()
        except TimeoutExpired:
            pass

        cprint("Started database...", "yellow")
        client = pymongo.MongoClient()
        db = client.image_database
        images = db.images

    # Create index on hash field
    images.create_index([("hashes", pymongo.ASCENDING)], unique=False)
    yield images

    client.close()

    if p is not None:
        cprint("Stopped database...", "yellow")
        p.terminate()


def get_files(path: str):
    """
    Check path recursively for files and yield full path.

    :param path:
    :return: yield absolute path
    """
    if os.path.isfile(path):
        yield path

    path = os.path.abspath(path)
    for root, _, files in os.walk(path):
        for file in files:
            file = os.path.join(root, file)
            yield file


def hash_file(file_path: str):
    """Hash file with all hashers"""
    hashes = []
    meta = {}
    hashers = get_hashers()

    try:
        for hasher in hashers:
            if hasher.is_applicable(file_path):
                with open(file_path, 'rb') as file_object:
                    try:
                        (new_hashes, new_meta) = hasher.hash(file_object)
                        hashes = hashes + new_hashes
                        meta = meta | new_meta
                    except Exception as e:
                        cprint(f'\tHashing error "{e}" of {type(hasher).__name__} at {file_path}',
                               "red")

        cprint(f'\tHashed {file_path}', "blue")
    except OSError:
        cprint(f'\tUnable to open {file_path}', "red")
        return None

    if len(hashes) == 0:
        return None

    return file_path, (
        hashes,
        meta
    )


def hash_files_parallel(files, num_processes=None):
    """Hash files in parallel in subprocesses"""
    with concurrent.futures.ProcessPoolExecutor(max_workers=num_processes) as executor:
        for result in executor.map(hash_file, files):
            if result is not None:
                yield result


def _add_to_database(file_path: str, hashes_meta: tuple, db):
    """Add hashes and meta information of a file to database"""
    (hashes, meta) = hashes_meta
    try:
        db.insert_one({"_id": file_path,
                       "hashes": hashes,
                       "meta": meta,
                       })
    except pymongo.errors.DuplicateKeyError:
        cprint(f'Duplicate key: {file_path}', "red")


def _in_database(file, db):
    """Return if file exists in database"""
    return db.count_documents({"_id": file}) > 0


def new_files(files, db):
    """yield only new files, already hashed files are skipped"""
    for file_path in files:
        if _in_database(file_path, db):
            cprint(f'\tAlready hashed {file_path}', "green")
        else:
            yield file_path


def add(paths, db, num_processes=None):
    """Loop through files and add hash them"""
    for path in paths:
        cprint(f'Hashing {path}', "blue")
        files = get_files(path)
        files = new_files(files, db)

        for result in hash_files_parallel(files, num_processes):
            _add_to_database(*result, db=db)

        cprint("...done", "blue")


def remove(paths, db):
    """Remove file from database"""
    for path in paths:
        files = get_files(path)
        for file in files:
            remove_file(file, db)


def remove_file(file, db):
    """Remove file from database"""
    db.delete_one({'_id': file})


def clear(db):
    """Clear database"""
    db.drop()


def show(db):
    """Show all files from the databse"""
    total = db.count_documents({})
    pprint(list(db.find()))
    print(f'Total: {total}')


def cleanup(db):
    """Clean disappeared files from the database"""
    count = 0
    files = db.find()
    for _id in files:
        file_name = _id['_id']
        if not os.path.exists(file_name):
            remove_file(file_name, db)
            count += 1
    cprint(f'Cleanup removed {count} files', 'yellow')


def same_time(dup):
    """Check if capture_time meta attribute is the same"""
    items = dup['items']

    if len({(i['meta']['capture_time'] if 'capture_time' in i['meta'] else '') for i in items}) > 1:
        return False

    return True


def find(db, match_time=False):
    """Find duplictes by equal hashes"""
    dups = db.aggregate([
        {"$unwind": "$hashes"},
        {
            "$group": {
                "_id": "$hashes",
                "total": {"$sum": 1},
                "file_size": {"$max": "$meta.file_size"},
                "items": {
                    "$push": {
                        "file_name": "$_id",
                        "meta": "$meta",
                    }
                }
            }
        },
        {
            "$match": {
                "total": {"$gt": 1}
            }
        },
        {"$sort": {"file_size": -1}}
    ])

    if match_time:
        dups = (d for d in dups if same_time(d))

    return make_duplcated_groups_unique(dups)


def make_duplcated_groups_unique(dups):
    """Deduplicate results by removing same groups of duplicates matched by multiple hashes"""
    cprint('Removing same groups of duplicates having multiple matching hashes...')
    deduplicated = []
    unique_groups = set()
    for dup in dups:
        group_ids = ' '.join(sorted(x['file_name'] for x in dup['items']))
        if group_ids not in unique_groups:
            unique_groups.add(group_ids)
            deduplicated.append(dup)

    return deduplicated


def _build_binary_tree(cursor, pbp: ProgressBarPrinter) -> pybktree.BKTree:
    """Build binary tree for fuzzy searches."""
    cprint('Building fuzzy tree...')
    # Build a tree
    tree = pybktree.BKTree(pybktree.hamming_distance)
    for document in cursor:
        pbp.print().inc()
        for doc_hash in document['hashes']:
            int_hash = int.from_bytes(doc_hash, "big")
            tree.add(int_hash)

    return tree


def _get_similar_hashes(doc_hashes, tree: pybktree.BKTree, threshold: int) -> set:
    """Get similar hashes from tree."""
    similar = {}
    for doc_hash in doc_hashes:
        int_hash = int.from_bytes(doc_hash, "big")
        new_similar = tree.find(int_hash, threshold)
        if len(new_similar) > 1:  # length == 1 when it is exact match to itself
            new_similar = set(new_similar)  # Make unique
            similar[doc_hash] = list(
                map(lambda item: binascii.unhexlify(hex(item[1])[2:]), new_similar)
            )

    return similar


def _get_similars_from_tree(db, tree: pybktree.BKTree, cursor,
                            pbp: ProgressBarPrinter, threshold: int):
    """Get fuzzy matched semilar duplicates."""
    cprint('\rSearching duplicates...')
    dups = []
    deduplicated = set()

    for document in cursor:
        pbp.print().inc()

        hashes_to_dedup = set(document['hashes']) - deduplicated
        deduplicated.update(document['hashes'])

        similar_hashes = _get_similar_hashes(hashes_to_dedup, tree, threshold)

        if len(similar_hashes) > 0:
            max_size = document['meta']['file_size']
            for doc_hashes in similar_hashes.values():
                deduplicated.update(doc_hashes)

                similars = []
                similars_name = set()
                for item in db.find({'hashes': {'$in': doc_hashes}}):
                    if item['_id'] in similars_name:
                        continue
                    similars_name.add(item['_id'])
                    item['file_name'] = item['_id']
                    similars.append(item)
                    max_size = max_size if item['meta']['file_size'] <= max_size \
                        else item['meta']['file_size']

                dups.append({
                    '_id': list(similar_hashes.keys()),
                    'total': len(similars),
                    'items': similars,
                    'file_size': max_size
                })

    return make_duplcated_groups_unique(dups)


def find_threshold(db, threshold=1):
    """Find duplicates by number of bits of Humming distance"""
    cprint('Finding fuzzy duplicates, it might take a while...')

    cnt = db.count_documents({})
    all_documents = db.find()

    pbp = ProgressBarPrinter(cnt)

    tree = _build_binary_tree(all_documents, pbp)
    pbp.reset()
    all_documents.rewind()
    return _get_similars_from_tree(db, tree, all_documents, pbp, threshold)


def delete_duplicates(duplicates, db):
    """Delete duplicates except the first one"""
    results = [delete_duplicate_file(x['file_name'], db)
               for dup in duplicates for x in dup['items'][1:]]
    cprint(f'Deleted {results.count(True)}/{len(results)} files', 'yellow')


def delete_duplicate_file(file_name, db, trash="./Trash/"):
    """Delete duplicated file and from the database"""
    cprint(f'Moving {file_name} to {trash}', 'yellow')
    if not os.path.exists(trash):
        os.makedirs(trash)
    try:
        shutil.move(file_name, trash + os.path.basename(file_name))
        remove_file(file_name, db)
    except FileNotFoundError:
        cprint(f'File not found {file_name}', 'red')
        return False
    except Exception as e:
        cprint(f'Error: {str(e)}', 'red')
        return False

    return True


def transpose_duplicagtes(duplicates):
    """Transpose duplictes to render in columns"""
    for group in duplicates:
        items_clount = len(group['items'])
        row = {
            'id': [''] * items_clount,
            'file_name': [''] * items_clount,
        }
        index = 0
        for image in group['items']:
            row['id'][index] = image['file_name']
            row['file_name'][index] = image['file_name']
            for key, value in image['meta'].items():
                if key not in row:
                    row[key] = [''] * items_clount
                row[key][index] = value
            index += 1
        group['items'] = row

    return duplicates


def display_duplicates(duplicates, db, trash="./Trash/"):
    """Displays duplicates in browser"""
    duplicates = transpose_duplicagtes(duplicates)
    app = Flask(__name__)
    CORS(app)

    def render(duplicates, current, total):
        env = Environment(loader=FileSystemLoader('template'))
        env.filters['hash'] = hash
        template = env.get_template('index.html')
        return template.render(duplicates=duplicates,
                               current=current,
                               total=total)

    with TemporaryDirectory() as folder:
        if len(duplicates) == 0:
            env = Environment(loader=FileSystemLoader('template'))
            template = env.get_template('no_duplicates.html')
            with open(f'{folder}/0.html', 'w', encoding="utf-8") as f:
                f.write(template.render())

        else:
            # Generate all of the HTML files
            chunk_size = 25
            for i, dups_page in enumerate(chunked(duplicates, chunk_size)):
                with open(f'{folder}/{i}.html', 'w', encoding="utf-8") as f:
                    f.write(render(dups_page,
                                   current=i,
                                   total=math.ceil(len(duplicates) / chunk_size)
                                   )
                            )

        webbrowser.open(f'file://{folder}/0.html')

        @app.route('/picture/<path:file_name>', methods=['DELETE'])
        def delete_picture_(file_name, trash=trash):
            return str(delete_duplicate_file('/' + file_name, db, trash))

        @app.route('/heic-transform/<path:file_name>', methods=['GET'])
        def transcode_heic_(file_name):
            heif_image = Image.open('/' + file_name)
            encoded = io.BytesIO()
            heif_image.save(encoded, format='JPEG')
            return Response(encoded.getvalue(), mimetype='image/jpeg')

        app.run()


if __name__ == '__main__':
    from docopt import docopt
    args = docopt(__doc__)

    if args['--trash']:
        TRASH = args['--trash']
    else:
        TRASH = "./Trash/"

    if args['--db']:
        DB_PATH = args['--db']
    else:
        DB_PATH = "./db"

    if args['--parallel']:
        NUM_PROCESSES = int(args['--parallel'])
    else:
        NUM_PROCESSES = None

    with connect_to_db(db_conn_string=DB_PATH) as main_db:
        if args['add']:
            add(args['<path>'], main_db, NUM_PROCESSES)
        elif args['remove']:
            remove(args['<path>'], main_db)
        elif args['clear']:
            clear(main_db)
        elif args['cleanup']:
            cleanup(main_db)
        elif args['show']:
            show(main_db)
        elif args['find']:
            if args['--threshold'] is not None:
                main_dups = find_threshold(main_db, int(args['--threshold']))
            else:
                main_dups = find(main_db, args['--match-time'])

            if args['--delete']:
                delete_duplicates(main_dups, main_db)
            elif args['--print']:
                pprint(main_dups)
                print(f'Number of duplicates: {len(main_dups)}')
            else:
                display_duplicates(main_dups, db=main_db)