ref: Update package mngt and optimize the vector store functions (#115)

* ref: Update download and hash chunk sizes to speed up

* build: Adopt uv with uv.lock and drop requirements.txt

* ref: Centralize softmax helper and minor cleanups

.github/workflows/ci.yml

@@ -52,26 +52,23 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v5
 
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
+          enable-cache: true
           python-version: ${{ matrix.python-version }}
-          cache: "pip"
 
       - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          python -m pip install ".[cpu,dev]"
+        run: uv sync --locked --extra cpu --extra dev
 
       - name: Check ONNX Runtime providers
-        run: |
-          python -c "import onnxruntime as ort; print('Available providers:', ort.get_available_providers())"
+        run: uv run python -c "import onnxruntime as ort; print('Available providers:', ort.get_available_providers())"
 
       - name: Run tests
-        run: pytest -v --tb=short
+        run: uv run pytest -v --tb=short
 
       - name: Test package imports
-        run: python -c "import uniface; print(f'uniface {uniface.__version__} loaded with {len(uniface.__all__)} exports')"
+        run: uv run python -c "import uniface; print(f'uniface {uniface.__version__} loaded with {len(uniface.__all__)} exports')"
 
   build:
     runs-on: ubuntu-latest

.github/workflows/docs.yml

@@ -14,19 +14,19 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
+          enable-cache: true
           python-version: "3.11"
 
       - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install mkdocs-material pymdown-extensions mkdocs-git-committers-plugin-2 mkdocs-git-revision-date-localized-plugin
+        run: uv sync --locked --extra docs
 
       - name: Build docs
         env:
           MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
-        run: mkdocs build --strict
+        run: uv run mkdocs build --strict
 
       - name: Deploy to GitHub Pages
         uses: peaceiris/actions-gh-pages@v4

.github/workflows/pipeline.yml

@@ -68,19 +68,17 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v5
 
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
+          enable-cache: true
           python-version: ${{ matrix.python-version }}
-          cache: 'pip'
 
       - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          python -m pip install ".[cpu,dev]"
+        run: uv sync --locked --extra cpu --extra dev
 
       - name: Run tests
-        run: pytest -v --tb=short
+        run: uv run pytest -v --tb=short
 
   release:
     runs-on: ubuntu-latest
@@ -198,20 +196,19 @@ jobs:
           ref: v${{ inputs.version }}
           fetch-depth: 0
 
-      - name: Set up Python
-        uses: actions/setup-python@v6
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
+          enable-cache: true
           python-version: "3.11"
 
       - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install mkdocs-material pymdown-extensions mkdocs-git-committers-plugin-2 mkdocs-git-revision-date-localized-plugin
+        run: uv sync --locked --extra docs
 
       - name: Build docs
         env:
           MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
-        run: mkdocs build --strict
+        run: uv run mkdocs build --strict
 
       - name: Deploy to GitHub Pages
         uses: peaceiris/actions-gh-pages@v4

CONTRIBUTING.md

@@ -21,25 +21,31 @@ Thank you for considering contributing to UniFace! We welcome contributions of a
 
 ## Development Setup
 
+We use [uv](https://docs.astral.sh/uv/) for reproducible dev installs. The committed `uv.lock` pins every transitive dependency so contributors and CI resolve to identical versions.
+
 ```bash
+# Install uv (https://docs.astral.sh/uv/getting-started/installation/)
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
 git clone https://github.com/yakhyo/uniface.git
 cd uniface
-pip install -e ".[dev]"
+
+# Sync runtime + cpu + dev extras from uv.lock (use --extra gpu instead of cpu for CUDA)
+uv sync --extra cpu --extra dev
 ```
 
+`uv sync` creates a project-local `.venv/` and installs everything pinned in `uv.lock`. Run commands with `uv run <cmd>` (e.g. `uv run pytest`), or activate the venv with `source .venv/bin/activate`.
+
 ### Setting Up Pre-commit Hooks
 
-We use [pre-commit](https://pre-commit.com/) to ensure code quality and consistency. Install and configure it:
+We use [pre-commit](https://pre-commit.com/) to ensure code quality and consistency. `pre-commit` is included in the `[dev]` extra, so it's already installed after `uv sync`.
 
 ```bash
-# Install pre-commit
-pip install pre-commit
-
 # Install the git hooks
-pre-commit install
+uv run pre-commit install
 
 # (Optional) Run against all files
-pre-commit run --all-files
+uv run pre-commit run --all-files
 ```
 
 Once installed, pre-commit will automatically run on every commit to check:

docs/contributing.md

@@ -6,16 +6,20 @@ Thank you for contributing to UniFace!
 
 ## Quick Start
 
+We use [uv](https://docs.astral.sh/uv/) for reproducible dev installs (lockfile-pinned).
+
 ```bash
+# Install uv first: https://docs.astral.sh/uv/getting-started/installation/
+
 # Clone
 git clone https://github.com/yakhyo/uniface.git
 cd uniface
 
-# Install dev dependencies
-pip install -e ".[dev]"
+# Install runtime + cpu + dev extras from uv.lock (--extra gpu for CUDA)
+uv sync --extra cpu --extra dev
 
 # Run tests
-pytest
+uv run pytest
 ```
 
 ---
@@ -39,10 +43,11 @@ ruff check . --fix
 
 ## Pre-commit Hooks
 
+`pre-commit` is included in the `[dev]` extra, so `uv sync` already installs it.
+
 ```bash
-pip install pre-commit
-pre-commit install
-pre-commit run --all-files
+uv run pre-commit install
+uv run pre-commit run --all-files
 ```
 
 ---

pyproject.toml

@@ -51,14 +51,20 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-cpu = ["onnxruntime>=1.16.0"]
-gpu = ["onnxruntime-gpu>=1.16.0"]
+cpu = [
+    "onnxruntime>=1.16.0; python_version >= '3.11'",
+    "onnxruntime>=1.16.0,<1.24; python_version < '3.11'",
+]
+gpu = [
+    "onnxruntime-gpu>=1.16.0; python_version >= '3.11'",
+    "onnxruntime-gpu>=1.16.0,<1.24; python_version < '3.11'",
+]
 dev = ["pytest>=7.0.0", "ruff>=0.4.0", "pre-commit>=3.0.0"]
 docs = [
-    "mkdocs-material>=9.0",
-    "pymdown-extensions>=10.0",
-    "mkdocs-git-committers-plugin-2>=1.0",
-    "mkdocs-git-revision-date-localized-plugin>=2.0",
+    "mkdocs-material",
+    "pymdown-extensions",
+    "mkdocs-git-committers-plugin-2",
+    "mkdocs-git-revision-date-localized-plugin",
 ]
 
 [project.urls]

requirements.txt

@@ -1,9 +0,0 @@
-numpy>=1.21.0
-opencv-python>=4.5.0
-scikit-image>=0.22.0
-scipy>=1.7.0
-requests>=2.28.0
-tqdm>=4.64.0
-# Install ONE of the following (not both):
-# onnxruntime>=1.16.0        # CPU / Apple Silicon  →  pip install uniface[cpu]
-# onnxruntime-gpu>=1.16.0    # NVIDIA CUDA          →  pip install uniface[gpu]

tests/test_draw.py

@@ -1,61 +0,0 @@
-# Copyright 2025-2026 Yakhyokhuja Valikhujaev
-# Author: Yakhyokhuja Valikhujaev
-# GitHub: https://github.com/yakhyo
-
-from __future__ import annotations
-
-import numpy as np
-
-from uniface.draw import draw_gaze
-
-
-def _compute_gaze_delta(bbox: np.ndarray, pitch: float, yaw: float) -> tuple[int, int]:
-    """Replicate draw_gaze dx/dy math for verification."""
-    x_min, _, x_max, _ = map(int, bbox[:4])
-    length = x_max - x_min
-    dx = int(-length * np.sin(yaw) * np.cos(pitch))
-    dy = int(-length * np.sin(pitch))
-    return dx, dy
-
-
-def test_draw_gaze_yaw_only_moves_horizontally():
-    """Yaw-only input (pitch=0) should produce horizontal displacement only."""
-    image = np.zeros((200, 200, 3), dtype=np.uint8)
-    bbox = np.array([50, 50, 150, 150], dtype=np.float32)
-
-    yaw = 0.5
-    pitch = 0.0
-    dx, dy = _compute_gaze_delta(bbox, pitch, yaw)
-
-    assert dx != 0, 'Yaw-only should produce horizontal displacement'
-    assert dy == 0, 'Yaw-only should produce zero vertical displacement'
-
-    # Should not raise
-    draw_gaze(image, bbox, pitch, yaw, draw_bbox=False, draw_angles=False)
-
-
-def test_draw_gaze_pitch_only_moves_vertically():
-    """Pitch-only input (yaw=0) should produce vertical displacement only."""
-    image = np.zeros((200, 200, 3), dtype=np.uint8)
-    bbox = np.array([50, 50, 150, 150], dtype=np.float32)
-
-    yaw = 0.0
-    pitch = 0.5
-    dx, dy = _compute_gaze_delta(bbox, pitch, yaw)
-
-    assert dx == 0, 'Pitch-only should produce zero horizontal displacement'
-    assert dy != 0, 'Pitch-only should produce vertical displacement'
-
-    # Should not raise
-    draw_gaze(image, bbox, pitch, yaw, draw_bbox=False, draw_angles=False)
-
-
-def test_draw_gaze_modifies_image():
-    """draw_gaze should modify the image in place."""
-    image = np.zeros((200, 200, 3), dtype=np.uint8)
-    bbox = np.array([50, 50, 150, 150], dtype=np.float32)
-
-    original = image.copy()
-    draw_gaze(image, bbox, 0.3, 0.3)
-
-    assert not np.array_equal(image, original), 'draw_gaze should modify the image'

tools/parse.py

@@ -198,7 +198,10 @@ def main():
     parser_arg.add_argument('--source', type=str, required=True, help='Image/video path or camera ID (0, 1, ...)')
     parser_arg.add_argument('--save-dir', type=str, default='outputs', help='Output directory')
     parser_arg.add_argument(
-        '--model', type=str, default=ParsingWeights.RESNET18, choices=[ParsingWeights.RESNET18, ParsingWeights.RESNET34]
+        '--model',
+        type=ParsingWeights,
+        default=ParsingWeights.RESNET18,
+        choices=list(ParsingWeights),
     )
     parser_arg.add_argument(
         '--expand-ratio',

uniface/analyzer.py

@@ -113,9 +113,10 @@ class FaceAnalyzer:
         return faces
 
     def __repr__(self) -> str:
-        parts = [f'FaceAnalyzer(detector={self.detector.__class__.__name__}']
+        parts = [f'detector={self.detector.__class__.__name__}']
         if self.recognizer:
             parts.append(f'recognizer={self.recognizer.__class__.__name__}')
-        for attr in self.attributes:
-            parts.append(f'{attr.__class__.__name__}')
-        return ', '.join(parts) + ')'
+        if self.attributes:
+            attr_names = ', '.join(attr.__class__.__name__ for attr in self.attributes)
+            parts.append(f'attributes=[{attr_names}]')
+        return f'FaceAnalyzer({", ".join(parts)})'

uniface/attribute/fairface.py

@@ -7,6 +7,7 @@ import cv2
 import numpy as np
 
 from uniface.attribute.base import Attribute
+from uniface.common import softmax
 from uniface.constants import FairFaceWeights
 from uniface.log import Logger
 from uniface.model_store import verify_model_weights
@@ -150,9 +151,9 @@ class FairFace(Attribute):
         race_logits, gender_logits, age_logits = prediction
 
         # Apply softmax
-        race_probs = self._softmax(race_logits[0])
-        gender_probs = self._softmax(gender_logits[0])
-        age_probs = self._softmax(age_logits[0])
+        race_probs = softmax(race_logits[0])
+        gender_probs = softmax(gender_logits[0])
+        age_probs = softmax(age_logits[0])
 
         # Get predictions
         race_idx = int(np.argmax(race_probs))
@@ -186,9 +187,3 @@ class FairFace(Attribute):
         face.age_group = result.age_group
         face.race = result.race
         return result
-
-    @staticmethod
-    def _softmax(x: np.ndarray) -> np.ndarray:
-        """Compute softmax values for numerical stability."""
-        exp_x = np.exp(x - np.max(x))
-        return exp_x / np.sum(exp_x)

uniface/common.py

@@ -19,6 +19,7 @@ __all__ = [
     'letterbox_resize',
     'non_max_suppression',
     'resize_image',
+    'softmax',
     'xyxy_to_cxcywh',
 ]
 
@@ -63,6 +64,21 @@ def resize_image(
     return image, resize_factor
 
 
+def softmax(x: np.ndarray, axis: int = -1) -> np.ndarray:
+    """Compute the numerically stable softmax of an array along ``axis``.
+
+    Args:
+        x: Input array.
+        axis: Axis along which softmax is computed. Defaults to the last axis.
+
+    Returns:
+        Array of the same shape as *x* with values in ``[0, 1]`` summing to 1
+        along *axis*.
+    """
+    exp_x = np.exp(x - np.max(x, axis=axis, keepdims=True))
+    return exp_x / np.sum(exp_x, axis=axis, keepdims=True)
+
+
 def xyxy_to_cxcywh(bboxes: np.ndarray) -> np.ndarray:
     """Convert bounding boxes from ``[x1, y1, x2, y2]`` to ``[cx, cy, w, h]``.
 

uniface/constants.py

@@ -469,4 +469,5 @@ MODEL_REGISTRY: dict[Enum, ModelInfo] = {
 MODEL_URLS: dict[Enum, str] = {k: v.url for k, v in MODEL_REGISTRY.items()}
 MODEL_SHA256: dict[Enum, str] = {k: v.sha256 for k, v in MODEL_REGISTRY.items()}
 
-CHUNK_SIZE = 8192
+DOWNLOAD_CHUNK_SIZE = 256 * 1024  # 256 KiB
+HASH_CHUNK_SIZE = 1024 * 1024  # 1 MiB

uniface/detection/yolov8.py

@@ -13,7 +13,7 @@ from typing import Any, Literal
 
 import numpy as np
 
-from uniface.common import letterbox_resize, non_max_suppression
+from uniface.common import letterbox_resize, non_max_suppression, softmax
 from uniface.constants import YOLOv8FaceWeights
 from uniface.log import Logger
 from uniface.model_store import verify_model_weights
@@ -171,12 +171,6 @@ class YOLOv8Face(BaseDetector):
         """
         return self.session.run(self.output_names, {self.input_names: input_tensor})
 
-    @staticmethod
-    def _softmax(x: np.ndarray, axis: int = -1) -> np.ndarray:
-        """Compute softmax values for array x along specified axis."""
-        exp_x = np.exp(x - np.max(x, axis=axis, keepdims=True))
-        return exp_x / np.sum(exp_x, axis=axis, keepdims=True)
-
     def postprocess(
         self,
         predictions: list[np.ndarray],
@@ -224,7 +218,7 @@ class YOLOv8Face(BaseDetector):
 
             # Decode bounding boxes from DFL
             bbox_pred = bbox_pred.reshape(-1, 4, 16)
-            bbox_dist = self._softmax(bbox_pred, axis=-1) @ np.arange(16)
+            bbox_dist = softmax(bbox_pred, axis=-1) @ np.arange(16)
 
             # Convert distances to xyxy format
             x1 = (grid_x - bbox_dist[:, 0]) * stride

uniface/draw.py

@@ -677,14 +677,10 @@ def vis_parsing_maps(
     segmentation_mask = segmentation_mask.copy().astype(np.uint8)
 
     # Create a color mask
-    segmentation_mask_color = np.zeros((segmentation_mask.shape[0], segmentation_mask.shape[1], 3))
-
-    num_classes = np.max(segmentation_mask)
-    for class_index in range(1, num_classes + 1):
-        class_pixels = np.where(segmentation_mask == class_index)
-        segmentation_mask_color[class_pixels[0], class_pixels[1], :] = FACE_PARSING_COLORS[class_index]
-
-    segmentation_mask_color = segmentation_mask_color.astype(np.uint8)
+    max_class = int(segmentation_mask.max())
+    palette = np.zeros((max(max_class + 1, len(FACE_PARSING_COLORS)), 3), dtype=np.uint8)
+    palette[: len(FACE_PARSING_COLORS)] = FACE_PARSING_COLORS
+    segmentation_mask_color = palette[segmentation_mask]
 
     # Convert image to BGR format for blending
     bgr_image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

uniface/gaze/models.py

@@ -6,6 +6,7 @@
 import cv2
 import numpy as np
 
+from uniface.common import softmax
 from uniface.constants import GazeWeights
 from uniface.log import Logger
 from uniface.model_store import verify_model_weights
@@ -142,11 +143,6 @@ class MobileGaze(BaseGazeEstimator):
 
         return image
 
-    def _softmax(self, x: np.ndarray) -> np.ndarray:
-        """Apply softmax along axis 1."""
-        e_x = np.exp(x - np.max(x, axis=1, keepdims=True))
-        return e_x / e_x.sum(axis=1, keepdims=True)
-
     def postprocess(self, outputs: tuple[np.ndarray, np.ndarray]) -> GazeResult:
         """
         Postprocess raw model outputs into gaze angles.
@@ -164,8 +160,8 @@ class MobileGaze(BaseGazeEstimator):
         yaw_logits, pitch_logits = outputs
 
         # Convert logits to probabilities
-        yaw_probs = self._softmax(yaw_logits)
-        pitch_probs = self._softmax(pitch_logits)
+        yaw_probs = softmax(yaw_logits)
+        pitch_probs = softmax(pitch_logits)
 
         # Compute expected bin index (soft-argmax)
         yaw_deg = np.sum(yaw_probs * self._idx_tensor, axis=1) * self._binwidth - self._angle_offset

uniface/log.py

@@ -2,12 +2,6 @@
 # Author: Yakhyokhuja Valikhujaev
 # GitHub: https://github.com/yakhyo
 
-"""Logging utilities for UniFace.
-
-This module provides a centralized logger for the UniFace library,
-allowing users to enable verbose logging when debugging or developing.
-"""
-
 from __future__ import annotations
 
 import logging

uniface/model_store.py

@@ -2,12 +2,6 @@
 # Author: Yakhyokhuja Valikhujaev
 # GitHub: https://github.com/yakhyo
 
-"""Model weight management for UniFace.
-
-This module handles downloading, caching, and verifying model weights
-using SHA-256 checksums for integrity validation.
-"""
-
 from __future__ import annotations
 
 from concurrent.futures import ThreadPoolExecutor, as_completed
@@ -159,7 +153,7 @@ def download_file(url: str, dest_path: str, timeout: int = 60, max_retries: int
                     unit_divisor=1024,
                 ) as progress,
             ):
-                for chunk in response.iter_content(chunk_size=const.CHUNK_SIZE):
+                for chunk in response.iter_content(chunk_size=const.DOWNLOAD_CHUNK_SIZE):
                     if chunk:
                         file.write(chunk)
                         progress.update(len(chunk))
@@ -178,7 +172,7 @@ def verify_file_hash(file_path: str, expected_hash: str) -> bool:
     """Compute the SHA-256 hash of the file and compare it with the expected hash."""
     file_hash = hashlib.sha256()
     with open(file_path, 'rb') as f:
-        for chunk in iter(lambda: f.read(const.CHUNK_SIZE), b''):
+        for chunk in iter(lambda: f.read(const.HASH_CHUNK_SIZE), b''):
             file_hash.update(chunk)
     actual_hash = file_hash.hexdigest()
     if actual_hash != expected_hash:
@@ -187,7 +181,7 @@ def verify_file_hash(file_path: str, expected_hash: str) -> bool:
 
 
 def download_models(
-    model_names: list[Enum], max_workers: int = 4, timeout: int = 60, max_retries: int = 3
+    model_names: list[Enum], max_workers: int | None = None, timeout: int = 60, max_retries: int = 3
 ) -> dict[Enum, str]:
     """Download and verify multiple models concurrently.
 
@@ -214,6 +208,17 @@ def download_models(
     results: dict[Enum, str] = {}
     errors: list[str] = []
 
+    if isinstance(max_workers, bool) or not isinstance(max_workers, int | None):
+        raise TypeError(f'max_workers must be int or None, got {type(max_workers).__name__}')
+
+    if max_workers is None or max_workers < 1:
+        if max_workers < 1:
+            Logger.info(f'max_workers must be >= 1, got {max_workers}; falling back to auto mode')
+        max_workers = min(os.cpu_count(), 8)  # at most 8
+
+    if max_workers < 1:
+        raise ValueError(f'max_workers must be >= 1, got {max_workers}')
+
     with ThreadPoolExecutor(max_workers=max_workers) as executor:
         future_to_model = {
             executor.submit(verify_model_weights, name, timeout=timeout, max_retries=max_retries): name

uniface/spoofing/minifasnet.py

@@ -6,6 +6,7 @@
 import cv2
 import numpy as np
 
+from uniface.common import softmax
 from uniface.constants import MiniFASNetWeights
 from uniface.log import Logger
 from uniface.model_store import verify_model_weights
@@ -179,11 +180,6 @@ class MiniFASNet(BaseSpoofer):
 
         return face
 
-    def _softmax(self, x: np.ndarray) -> np.ndarray:
-        """Apply softmax to logits along axis 1."""
-        e_x = np.exp(x - np.max(x, axis=1, keepdims=True))
-        return e_x / e_x.sum(axis=1, keepdims=True)
-
     def postprocess(self, outputs: np.ndarray) -> SpoofingResult:
         """
         Postprocess raw model outputs into prediction result.
@@ -197,7 +193,7 @@ class MiniFASNet(BaseSpoofer):
         Returns:
             SpoofingResult: Result containing is_real flag and confidence score.
         """
-        probs = self._softmax(outputs)
+        probs = softmax(outputs)
         label_idx = int(np.argmax(probs))
         confidence = float(probs[0, label_idx])
 

uniface/stores/faiss.py

@@ -115,7 +115,7 @@ class FAISS(BaseStore):
         return None, similarity
 
     def remove(self, key: str, value: Any) -> int:
-        """Remove all entries where ``metadata[key] == value`` and rebuild.
+        """Remove all entries where ``metadata[key] == value``.
 
         Args:
             key: Metadata key to match against.
@@ -126,22 +126,19 @@ class FAISS(BaseStore):
         """
         faiss = _import_faiss()
 
-        keep = [i for i, m in enumerate(self.metadata) if m.get(key) != value]
-        removed = len(self.metadata) - len(keep)
-        if removed == 0:
+        to_remove = [i for i, m in enumerate(self.metadata) if m.get(key) == value]
+        if not to_remove:
             return 0
 
-        if keep:
-            vectors = np.empty((len(keep), self.embedding_size), dtype=np.float32)
-            for dst, src in enumerate(keep):
-                self.index.reconstruct(src, vectors[dst])
-            new_index = faiss.IndexFlatIP(self.embedding_size)
-            new_index.add(vectors)
-        else:
-            new_index = faiss.IndexFlatIP(self.embedding_size)
+        ids = np.array(to_remove, dtype=np.int64)
+        self.index.remove_ids(faiss.IDSelectorBatch(ids))
 
-        self.index = new_index
-        self.metadata = [self.metadata[i] for i in keep]
+        # IndexFlatIP.remove_ids preserves the relative order of survivors,
+        # so deleting the same positions from metadata keeps them aligned.
+        drop = set(to_remove)
+        self.metadata = [m for i, m in enumerate(self.metadata) if i not in drop]
+
+        removed = len(to_remove)
         Logger.info('Removed %d entries where %s=%s (%d remaining)', removed, key, value, self.index.ntotal)
         return removed