From 8dbcb19b4361dcc15974058c5efd186ba5a6bb2b Mon Sep 17 00:00:00 2001
From: Brent Schroeter <contact@brentsch.com>
Date: Sun, 10 Aug 2025 12:27:39 -0700
Subject: [PATCH] init

---
 .gitignore      |   1 +
 .python-version |   1 +
 README.md       |  18 ++
 main.py         | 317 ++++++++++++++++++++++++
 mise.toml       |   9 +
 pyproject.toml  |  20 ++
 uv.lock         | 645 ++++++++++++++++++++++++++++++++++++++++++++++++
 7 files changed, 1011 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 .python-version
 create mode 100644 README.md
 create mode 100644 main.py
 create mode 100644 mise.toml
 create mode 100644 pyproject.toml
 create mode 100644 uv.lock

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..ea8c4bf
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+/target
diff --git a/.python-version b/.python-version
new file mode 100644
index 0000000..2c07333
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.11
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..d1cebcf
--- /dev/null
+++ b/README.md
@@ -0,0 +1,18 @@
+# MicroQA
+
+QA assistant for the Internet Archive's microfiche scanning team.
+
+## Usage
+
+Analyze page statistics for item:
+
+```sh
+echo 'micro_IA04244212_1665' | uv run main.py | jq
+```
+
+Paste item IDs from clipboard and summarize all (`tr` command collapses input to
+a single line so that items are summarized in parallel):
+
+```sh
+pbpaste | tr '\n' ',' | uv run main.py --summarize -workers 4 -v | jq
+```
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..372839d
--- /dev/null
+++ b/main.py
@@ -0,0 +1,317 @@
+import json
+import re
+import urllib.parse
+from argparse import ArgumentParser
+from csv import QUOTE_NONE
+from dataclasses import dataclass
+from io import BytesIO, StringIO
+from multiprocessing import Pool
+from multiprocessing.pool import ThreadPool
+from sys import stderr, stdin, stdout
+from zipfile import ZipFile
+
+import numpy as np
+import pandas as pd
+import pytesseract
+import requests
+from PIL import Image, ImageFilter
+
+
+def main():
+    parser = ArgumentParser()
+    parser.add_argument("--summarize", action="store_true")
+    parser.add_argument("-v", "--verbose", action="store_true")
+    parser.add_argument("-w", "--workers", type=int, default=1)
+    args = parser.parse_args()
+
+    # Process STDIN line by line, where each line contains one or more item IDs
+    # separated by whitespace.
+    for line in stdin:
+        item_ids = [value for value in re.split(r",|\s", line) if value]
+        with ThreadPool(args.workers) as pool:
+            if args.verbose:
+                print(f"Running with {args.workers} workers.", file=stderr)
+                stderr.flush()
+            if args.summarize:
+                pool.map(
+                    _summarize_item_to_stdout,
+                    [
+                        ItemTask(item_id=item_id, verbose=args.verbose)
+                        for item_id in item_ids
+                    ],
+                )
+            else:
+                pool.map(
+                    _analyze_item_to_stdout,
+                    [
+                        ItemTask(item_id=item_id, verbose=args.verbose)
+                        for item_id in item_ids
+                    ],
+                )
+
+
+@dataclass
+class ItemTask:
+    item_id: str
+    verbose: bool
+
+
+def _summarize_item_to_stdout(task):
+    item_id = task.item_id
+    verbose = task.verbose
+
+    if verbose:
+        print(f"Summarizing item {item_id}...", file=stderr)
+        stderr.flush()
+
+    analysis = analyze_item(item_id, verbose)
+
+    # 3 or more blank pages in a row is a flag.
+    CONSECUTIVE_BLANKS_THRESHOLD = 3
+    if len(analysis["pages"]) >= CONSECUTIVE_BLANKS_THRESHOLD:
+        consecutive_blanks = [page["blank"] for page in analysis["pages"]]
+        for _ in range(1, CONSECUTIVE_BLANKS_THRESHOLD):
+            consecutive_blanks = [
+                value and consecutive_blanks[i]
+                for i, value in enumerate(consecutive_blanks[1:])
+            ]
+        consecutive_blanks = [
+            i + 2  # +1 to account for enumeration offset, and +1 to 1-index
+            for i, value in enumerate(consecutive_blanks[1:])
+            if value and not consecutive_blanks[i]
+        ]
+    else:
+        consecutive_blanks = []
+
+    # 3 or more blank pages in a row is a flag.
+    CONSECUTIVE_BLURRY_THRESHOLD = 3
+    SHARPNESS_THRESHOLD = 0.08
+    if len(analysis["pages"]) >= CONSECUTIVE_BLURRY_THRESHOLD:
+        consecutive_blurry = [
+            page["sharpness"] < SHARPNESS_THRESHOLD for page in analysis["pages"]
+        ]
+        for _ in range(1, CONSECUTIVE_BLURRY_THRESHOLD):
+            consecutive_blurry = [
+                value and consecutive_blurry[i]
+                for i, value in enumerate(consecutive_blurry[1:])
+            ]
+        consecutive_blurry = [
+            i + 2  # +1 to account for enumeration offset, and +1 to 1-index
+            for i, value in enumerate(consecutive_blurry[1:])
+            if value and not consecutive_blurry[i]
+        ]
+    else:
+        consecutive_blurry = []
+
+    check_orientation = [
+        i + 1
+        for i, page in enumerate(analysis["pages"])
+        if not page["ocr_orientation_match"]
+    ]
+
+    if check_orientation or consecutive_blanks or consecutive_blurry:
+        print(
+            json.dumps(
+                {
+                    "item_id": item_id,
+                    "check_orientation": check_orientation,
+                    "consecutive_blanks": consecutive_blanks,
+                    "consecutive_blurry": consecutive_blurry,
+                }
+            )
+        )
+        stdout.flush()
+
+    if verbose:
+        print(f"Done summarizing item {item_id}.", file=stderr)
+        stderr.flush()
+
+
+def _analyze_item_to_stdout(task):
+    item_id = task.item_id
+    verbose = task.verbose
+
+    if verbose:
+        print(f"Analyzing item {item_id}...", file=stderr)
+        stderr.flush()
+
+    print(json.dumps(analyze_item(item_id, verbose)))
+    stdout.flush()
+
+    if verbose:
+        print(f"Done analyzing item {item_id}.", file=stderr)
+        stderr.flush()
+
+
+@dataclass
+class PageAnalysisTask:
+    im: Image.Image
+    page_index: int
+    file_name: str
+
+
+def _analyze_page(task):
+    im_original = task.im
+    page_index = task.page_index
+    file_name = task.file_name
+
+    im_cropped = im_original.crop(
+        (
+            im_original.size[0] * 0.1,
+            im_original.size[1] * 0.1,
+            im_original.size[0] * 0.9,
+            im_original.size[1] * 0.9,
+        )
+    )
+
+    is_blank = im_cropped.getextrema()[0] > 255 * 0.8
+
+    if is_blank:
+        max_sharpness = 1
+        ocr_orientation_match = True
+    else:
+        max_sharpness = 0.0
+        if im_cropped.size[0] < im_cropped.size[1]:
+            # Page is in portrait orientation.
+            segments_x = 2
+            segments_y = 3
+        else:
+            # Page is in landscape orientation.
+            segments_x = 3
+            segments_y = 2
+        for i in range(segments_x):
+            for j in range(segments_y):
+                max_sharpness = max(
+                    max_sharpness,
+                    analyze_sharpness(
+                        im_cropped.crop(
+                            (
+                                im_cropped.size[0] / segments_x * i,
+                                im_cropped.size[1] / segments_y * j,
+                                im_cropped.size[0] / segments_x * (i + 1),
+                                im_cropped.size[1] / segments_y * (j + 1),
+                            )
+                        )
+                    ),
+                )
+
+        n_words = []
+        for orientation in range(4):
+            im_rotated = im_original.rotate(90 * orientation)
+            ocr = pd.read_csv(
+                StringIO(pytesseract.image_to_data(im_rotated)),
+                sep="\t",
+                quoting=QUOTE_NONE,
+                dtype={"text": str},
+            ).fillna({"text": ""})
+            words = ocr[(ocr["conf"] > 90) & (ocr["width"] > ocr["height"])]
+            words = words[
+                words.apply(
+                    lambda row: re.fullmatch(r"[a-zA-Z]{4,}", row["text"]) is not None,
+                    axis=1,
+                )
+            ]
+            n_words.append(words.shape[0])
+            if len(words) > 50:
+                # Unlikely that another orientation will have more words, so
+                # stop eating up CPU unnecessarily.
+                break
+        ocr_orientation_match = np.max(n_words) == n_words[0]
+
+    return {
+        "blank": is_blank,
+        "file_name": file_name,
+        "ocr_orientation_match": ocr_orientation_match,
+        "page_index": page_index,
+        "size": im_original.size,
+        "sharpness": max_sharpness,
+    }
+
+
+def analyze_item(item_id, parallel=False, verbose=False):
+    escaped_item_id = urllib.parse.quote(item_id, safe="")
+
+    if verbose:
+        print("Downloading...", file=stderr)
+        stderr.flush()
+    page_nums_resp = requests.get(
+        f"https://archive.org/metadata/{escaped_item_id}/page_numbers/pages"
+    )
+    page_nums_resp.raise_for_status()
+    page_nums = page_nums_resp.json()["result"]
+
+    zip_resp = requests.get(
+        f"https://archive.org/download/{escaped_item_id}/{escaped_item_id}_jp2.zip"
+    )
+    zip_resp.raise_for_status()
+
+    if verbose:
+        print("Decompressing...", file=stderr)
+        stderr.flush()
+    tasks = []
+    with ZipFile(BytesIO(zip_resp.content)) as jp_zip:
+        for leaf_num, file_name in enumerate(sorted(jp_zip.namelist())):
+            for page_index, page_num_info in enumerate(page_nums):
+                if page_num_info["leafNum"] == leaf_num:
+                    # Stop iterating and keep page_index set to the current item.
+                    break
+            else:
+                # Set to -1 to indicate that leaf was not found in page_num list.
+                page_index = -1
+
+            if page_index != -1:
+                with jp_zip.open(file_name) as jp_file:
+                    im = Image.open(jp_file).convert("L")
+                    tasks.append(
+                        PageAnalysisTask(
+                            im=im, page_index=page_index, file_name=file_name
+                        )
+                    )
+
+    if verbose:
+        print(f"Processing {len(page_nums)} pages...", file=stderr)
+        stderr.flush()
+    if parallel:
+        # Parallelize image processing and OCR of pages across up to n cores.
+        N_PROCESSES = 8
+        with Pool(N_PROCESSES) as pool:
+            return {"pages": pool.map(_analyze_page, tasks)}
+    return {"pages": [_analyze_page(task) for task in tasks]}
+
+
+def analyze_sharpness(im):
+    """
+    Crudely quantifies the "sharpness" of edges in an image, on a scale of 0 to
+    1. The scale is not linear with respect to scan quality: anything above 0.1
+    is usually fine.
+    """
+    arr = np.asarray(im)
+
+    # Normalize contrast based on brightest and darkest pixels. For example,
+    # NORM_QUANTILE=0.1 will attempt to transform pixel values so that 80% fall
+    # between 10% brightness and 90% brightness. In practice, a value around
+    # 0.02 seems to work fairly well.
+    NORM_QUANTILE = 0.03
+    pixel_range = np.quantile(arr, 1.0 - NORM_QUANTILE) - np.quantile(
+        arr, NORM_QUANTILE
+    )
+    if pixel_range == 0:
+        arr_normalized = arr
+    else:
+        arr_normalized = arr * (1.0 - NORM_QUANTILE * 2) / pixel_range
+        arr_normalized = (
+            arr_normalized - np.quantile(arr_normalized, NORM_QUANTILE) + NORM_QUANTILE
+        )
+        arr_normalized = np.uint8(np.clip(arr_normalized, 0, 1) * 255)
+
+    # "Sharpness" is determined by measuring the median intensity of pixels
+    # near edges, after an edge detection filter has been applied to the image.
+    edges_arr = np.asarray(
+        Image.fromarray(arr_normalized).filter(ImageFilter.FIND_EDGES)
+    )
+    EDGE_THRESHOLD = 8
+    return np.median(edges_arr[edges_arr > EDGE_THRESHOLD]) / 255
+
+
+if __name__ == "__main__":
+    main()
diff --git a/mise.toml b/mise.toml
new file mode 100644
index 0000000..43f1713
--- /dev/null
+++ b/mise.toml
@@ -0,0 +1,9 @@
+[tools]
+jujutsu = "latest"
+uv = "latest"
+watchexec = "latest"
+
+[env]
+
+[settings]
+python.uv_venv_auto = true
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..d45cf91
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,20 @@
+[project]
+name = "microqa"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "numpy>=2.3.2",
+    "pandas>=2.3.1",
+    "pillow>=11.3.0",
+    "pytesseract>=0.3.13",
+    "requests>=2.32.4",
+]
+
+[dependency-groups]
+dev = [
+    "jedi>=0.19.2",
+    "python-lsp-server>=1.13.0",
+    "ruff>=0.12.8",
+]
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..512a406
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,645 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+    "python_full_version >= '3.12'",
+    "python_full_version < '3.12'",
+]
+
+[[package]]
+name = "black"
+version = "25.1.0"
+source = { registry = "https://pypi.org/simple" }
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+    { name = "click" },
+    { name = "mypy-extensions" },
+    { name = "packaging" },
+    { name = "pathspec" },
+    { name = "platformdirs" },
+]
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