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Merge pull request #1420 from PyWoody/image_utils
Optimizations for deepface.recognition.find, Optimization and New Iterator Functionality in image_utils
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5bab888411
@ -1,7 +1,7 @@
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# built-in dependencies
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import os
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import io
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from typing import List, Union, Tuple
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from typing import Generator, List, Union, Tuple
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import hashlib
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import base64
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from pathlib import Path
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@ -14,6 +14,10 @@ from PIL import Image
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from werkzeug.datastructures import FileStorage
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IMAGE_EXTS = {".jpg", ".jpeg", ".png"}
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PIL_EXTS = {"jpeg", "png"}
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def list_images(path: str) -> List[str]:
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"""
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List images in a given path
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@ -25,19 +29,31 @@ def list_images(path: str) -> List[str]:
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images = []
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for r, _, f in os.walk(path):
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for file in f:
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exact_path = os.path.join(r, file)
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ext_lower = os.path.splitext(exact_path)[-1].lower()
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if ext_lower not in {".jpg", ".jpeg", ".png"}:
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continue
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with Image.open(exact_path) as img: # lazy
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if img.format.lower() in {"jpeg", "png"}:
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images.append(exact_path)
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if os.path.splitext(file)[1].lower() in IMAGE_EXTS:
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exact_path = os.path.join(r, file)
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with Image.open(exact_path) as img: # lazy
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if img.format.lower() in PIL_EXTS:
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images.append(exact_path)
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return images
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def yield_images(path: str) -> Generator[str, None, None]:
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"""
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Yield images in a given path
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Args:
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path (str): path's location
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Yields:
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image (str): image path
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"""
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for r, _, f in os.walk(path):
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for file in f:
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if os.path.splitext(file)[1].lower() in IMAGE_EXTS:
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exact_path = os.path.join(r, file)
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with Image.open(exact_path) as img: # lazy
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if img.format.lower() in PIL_EXTS:
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yield exact_path
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def find_image_hash(file_path: str) -> str:
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"""
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Find the hash of given image file with its properties
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@ -136,7 +136,7 @@ def find(
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representations = []
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# required columns for representations
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df_cols = [
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df_cols = {
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"identity",
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"hash",
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"embedding",
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@ -144,7 +144,7 @@ def find(
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"target_y",
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"target_w",
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"target_h",
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]
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}
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# Ensure the proper pickle file exists
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if not os.path.exists(datastore_path):
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@ -157,18 +157,15 @@ def find(
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# check each item of representations list has required keys
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for i, current_representation in enumerate(representations):
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missing_keys = set(df_cols) - set(current_representation.keys())
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missing_keys = df_cols - set(current_representation.keys())
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if len(missing_keys) > 0:
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raise ValueError(
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f"{i}-th item does not have some required keys - {missing_keys}."
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f"Consider to delete {datastore_path}"
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)
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# embedded images
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pickled_images = [representation["identity"] for representation in representations]
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# Get the list of images on storage
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storage_images = image_utils.list_images(path=db_path)
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storage_images = set(image_utils.yield_images(path=db_path))
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if len(storage_images) == 0 and refresh_database is True:
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raise ValueError(f"No item found in {db_path}")
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@ -186,8 +183,13 @@ def find(
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# Enforce data consistency amongst on disk images and pickle file
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if refresh_database:
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new_images = set(storage_images) - set(pickled_images) # images added to storage
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old_images = set(pickled_images) - set(storage_images) # images removed from storage
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# embedded images
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pickled_images = {
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representation["identity"] for representation in representations
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}
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new_images = storage_images - pickled_images # images added to storage
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old_images = pickled_images - storage_images # images removed from storage
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# detect replaced images
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for current_representation in representations:
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@ -95,12 +95,23 @@ def test_filetype_for_find():
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def test_filetype_for_find_bulk_embeddings():
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imgs = image_utils.list_images("dataset")
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# List
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list_imgs = image_utils.list_images("dataset")
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assert len(imgs) > 0
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assert len(list_imgs) > 0
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# img47 is webp even though its extension is jpg
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assert "dataset/img47.jpg" not in imgs
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assert "dataset/img47.jpg" not in list_imgs
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# Generator
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gen_imgs = list(image_utils.yield_images("dataset"))
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assert len(gen_imgs) > 0
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# img47 is webp even though its extension is jpg
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assert "dataset/img47.jpg" not in gen_imgs
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assert gen_imgs == list_imgs
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def test_find_without_refresh_database():
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