Add Makefile

.gitignore

@@ -1,2 +1,5 @@
 __pycache__
 venv
+yolov3
+data/photos
+.*

Makefile

@@ -0,0 +1,13 @@
+WEIGHTS = yolov3-tiny
+#WEIGHTS = yolov3
+
+photocat :
+	echo "Download YOLOv3 network $(WEIGHTS)"
+	wget "https://pjreddie.com/media/files/$(WEIGHTS).weights" --header "Referer: pjreddie.com" -P yolov3
+	wget "https://raw.githubusercontent.com/eriklindernoren/PyTorch-YOLOv3/master/config/$(WEIGHTS).cfg" -P yolov3
+	echo "Install with pip etc TODO"
+
+clean :
+	rm -f yolov3/$(WEIGHTS).{weights,cfg}
+
+.PHONY : photocat clean

photocat.ipynb

@@ -0,0 +1,133 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Automatic photo categorization\n",
+    "\n",
+    "\n",
+    "Goals:\n",
+    "  - Categorize photos into semantically similar groups.\n",
+    "  - Mark similar photos for removal.\n",
+    "\n",
+    "\n",
+    "## Table of contents\n",
+    " 1. [Features](#features)\n",
+    " 2. [Clustering](#clustering)\n",
+    " 3. [Deduplication](#deduplication)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "from tqdm import tqdm\n",
+    "#from tqdm.notebook import tqdm\n",
+    "\n",
+    "from toolz import compose\n",
+    "from toolz.curried import map, filter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from photocat import fs, photo, group\n",
+    "\n",
+    "INPUT_DIR = 'data/photos'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name=\"features\"></a>\n",
+    "## Features\n",
+    "\n",
+    "Extract features from EXIF data and YOLOv3 output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def show_photos(photos, n_row, n_col, size=4):\n",
+    "    _, axs = plt.subplots(n_row, n_col, figsize=(n_col*size, n_row*size))\n",
+    "    axs = axs.flatten()\n",
+    "    for p, ax in zip(photos, axs):\n",
+    "        ax.imshow(p.thumbnail)\n",
+    "    plt.show()\n",
+    "\n",
+    "photos = compose(\n",
+    "    list,\n",
+    "    tqdm,\n",
+    "    map(lambda f: photo.Photo(f)),\n",
+    "    fs.list_images\n",
+    ")(INPUT_DIR)\n",
+    "\n",
+    "show_photos(photos[0:24], 6, 4)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name=\"clustering\"></a>\n",
+    "## Clustering\n",
+    "\n",
+    "Normalize features and cluster with DBSCAN."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name=\"deduplication\"></a>\n",
+    "## Deduplication\n",
+    "\n",
+    "Use eucledian distance between outputs of topmost YOLOv3 layers as a metric for photo similarity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

photocat/fs.py

@@ -1,4 +1,5 @@
 import os
+import datetime
 from toolz import compose
 from toolz.curried import filter, map
 
@@ -20,3 +21,9 @@ def list_images(folder):
         map(lambda f: os.path.join(folder, f)), 
         filter(lambda f: os.path.splitext(f)[-1].lower() in IMG_EXT)
     )(files)
+
+
+def last_modified(filename):
+    epoch = os.path.getmtime(filename)
+    return datetime.datetime.fromtimestamp(epoch)
+

photocat/group.py

@@ -1,30 +1,33 @@
-from collections import namedtuple
+import datetime
+from dataclasses import dataclass
 from itertools import groupby
 from toolz import curry, compose
 from toolz.curried import map, filter
 
+from photocat.photo import Photo
 
 
-PhotoGroup = namedtuple(
-    'PhotoGroup',
-    ['name', 'datetimes', 'photos']
-)
+@dataclass(init = False)
+class PhotoGroup:
+    name: str
+    min_datetime: datetime.datetime
+    max_datetime: datetime.datetime
+    photos: list[Photo]
+
+    def __init__(self, photos: list[Photo]):
+        self.min_datetime  = min(photos, key=lambda p: p.datetime).datetime
+        self.max_datetime = max(photos, key=lambda p: p.datetime).datetime
+        self.name = str(self.min_datetime) + '-' + str(self.max_datetime) # TODO
+        self.photos = photos
 
 
 @curry
 def _group(key, photos):
-    def create_group(k, photos):
-        min_dt = min(photos, key=lambda p: p.datetime).datetime
-        max_dt = max(photos, key=lambda p: p.datetime).datetime
-        name = str(min_dt) + '-' + str(max_dt) # TODO
-        return PhotoGroup(name, (min_dt, max_dt), photos)
-
     return [
-        create_group(k, list(v))
-        for k, v in groupby(sorted(photos, key=key), key=key)
+        PhotoGroup(list(v))
+        for _, v in groupby(sorted(photos, key=key), key=key)
     ]
 
 
-photos_by_month = _group(lambda p: p.datetime.month)
-
+photos_by_month = _group(lambda p: (p.datetime.year, p.datetime.month))
 

photocat/image.py

@@ -1,34 +0,0 @@
-import io
-from PIL import Image, ExifTags
-
-
-def read(filename, resize=None):
-    """Read and optionally resize an image."""
-    img = Image.open(filename)
-    cur_width, cur_height = img.size
-    if resize:
-        new_width, new_height = resize
-        scale = min(new_height/cur_height, new_width/cur_width)
-        img = img.resize((int(cur_width*scale), int(cur_height*scale)), Image.ANTIALIAS)
-    return img
-
-
-def read_exif(filename):
-    """Read EXIF data."""
-    img = Image.open(filename)
-    exif = img.getexif()
-    if exif is None:
-        raise Exception("No EXIF data for image %s" % filename)
-    return {
-        ExifTags.TAGS[k]: v
-        for k, v in exif.items()
-        if k in ExifTags.TAGS
-    }
-
-
-def to_bytes(img):
-    """Convert image to PNG format and return as byte-string object."""
-    bio = io.BytesIO()
-    img.save(bio, format="PNG")
-    return bio.getvalue()
-

photocat/main.py

@@ -1,24 +1,22 @@
+#!/usr/bin/env python3
+
 #import PySimpleGUI as sg
 import PySimpleGUIQt as sg
 import os
 from toolz import compose
 from toolz.curried import map
 
-import fs
-import image
-import photo
-import group
+from photocat import fs, photo, group
 
 
 MAX_ROWS = 100
-MAX_COLS = 5
-IMG_SIZE = (100, 100)
+MAX_COLS = 4
 
-NA_FILE = os.path.join(
+NA_FILENAME = os.path.join(
     os.path.dirname(__file__),
     'na.jpg'
 )
-NA_IMG = image.to_bytes(image.read(NA_FILE, resize=IMG_SIZE))
+NA_PHOTO = photo.Photo(NA_FILENAME)
 
 
 def main():
@@ -27,12 +25,12 @@ def main():
         [sg.Listbox(values=[], enable_events=True, size=(40,20),key='GROUP LIST')]
     ]
     image_view = [
-        [sg.Image(key='PHOTO %d' % (i*MAX_COLS+j), data=NA_IMG, visible=False, enable_events=True) for j in range(MAX_COLS)]
+        [sg.Image(key='PHOTO %d' % (i*MAX_COLS+j), data=NA_PHOTO.to_bytes(), visible=False, enable_events=True) for j in range(MAX_COLS)]
         for i in range(MAX_ROWS)
     ]
     group_view = [
         [sg.Text('Group: ')],
-        [sg.Column(image_view, scrollable=True, size=(650, 700), element_justification='l')]
+        [sg.Column(image_view, scrollable=True, size=(900, 700), element_justification='l')]
     ]
 
     layout = [[
@@ -52,7 +50,7 @@ def main():
             # Process input photos into groups
             groups = compose(
                 group.photos_by_month,
-                map(photo.read_photo), 
+                map(lambda f: photo.Photo(f)), 
                 fs.list_images
             )(values['FOLDER'])
             window['GROUP LIST'].update(values=[g.name for g in groups])
@@ -64,16 +62,13 @@ def main():
             # Assert number of photos
             n_photos = len(current_group.photos)
             assert n_photos <= MAX_ROWS*MAX_COLS
-            # Reset image view
+            # Update image view
             for idx in range(MAX_ROWS*MAX_COLS):
                 if idx < n_photos:
-                    window['PHOTO %d' % idx].update(data=NA_IMG, visible=True)
+                    p = current_group.photos[idx]
+                    window['PHOTO %d' % idx].update(data=p.to_bytes(), visible=True)
                 else:
                     window['PHOTO %d' % idx].update(visible=False)
-            # Load and display images
-            for idx, p in enumerate(current_group.photos):
-                img_data = image.to_bytes(image.read(p.filename, resize=IMG_SIZE))
-                window['PHOTO %d' % idx].update(data=img_data)
         elif event.startswith('PHOTO'):
             idx = int(event.split(' ')[-1])
             print("Selected photo %d" % idx)

photocat/photo.py

@@ -1,32 +1,62 @@
-import os
 import datetime
-from collections import namedtuple
-from dateutil import parser
+import io
+from dataclasses import dataclass
+from PIL import Image, ExifTags
 
-from image import read_exif
+from photocat import fs
 
 
-Photo = namedtuple(
-    'Photo',
-    ['filename', 'datetime', 'exif', 'features', 'selected']
-)
+IMG_SIZE = (200, 200)
+
+EXIF_DATETIME_KEY = 'DateTime'
+EXIF_DATETIME_FORMAT = '%Y:%m:%d %H:%M:%S'
 
 
 def _exif_dt(exif):
     try:
-        return parser.parse(exif['DateTimeOriginal'])
+        return datetime.datetime.strptime(
+            exif[EXIF_DATETIME_KEY],
+            EXIF_DATETIME_FORMAT
+        )
     except Exception:
         return None
 
-def _last_modified_dt(filename):
-    epoch = os.path.getmtime(filename)
-    return datetime.datetime.fromtimestamp(epoch)
 
+@dataclass(init = False)
+class Photo:
+    filename: str
+    exif: dict
+    datetime: datetime.datetime
+    thumbnail: Image
+    features: list
+    selected: bool = True
 
-def read_photo(filename):
-    exif = read_exif(filename)
-    print(filename, exif)
-    dt = _exif_dt(exif) or _last_modified_dt(filename)
-    features = [] # TODO
-    return Photo(filename, dt, exif, features, True)
+    def __init__(self, filename: str):
+        self.filename = filename
+        img = Image.open(filename)
+
+        exif = img.getexif()
+        if exif is None:
+            raise Exception("No EXIF data for image %s" % filename)
+        self.exif = {
+            ExifTags.TAGS[k]: v
+            for k, v in exif.items()
+            if k in ExifTags.TAGS
+        }
+
+        self.datetime = _exif_dt(self.exif) or fs.last_modified(filename)
+
+        cur_width, cur_height = img.size
+        new_width, new_height = IMG_SIZE
+        scale = min(new_height/cur_height, new_width/cur_width)
+        self.thumbnail = img.resize((int(cur_width*scale), int(cur_height*scale)), Image.ANTIALIAS)
+
+        self.features = [] # TODO
+        print("Loaded", filename, "at", self.datetime, "with exif", self.exif)
+
+    def to_bytes(self) -> bytes:
+        """Convert image to PNG format and return as byte-string object."""
+        bio = io.BytesIO()
+        self.thumbnail.save(bio, format="PNG")
+        return bio.getvalue()