9 Commits

Author SHA1 Message Date
Zach Nussbaum
d1cde9b608 fix: respect max output tokens 2025-11-04 13:16:57 -05:00
Vik Paruchuri
aabfed2ed3 Fix max repeats 2025-11-03 17:11:51 -05:00
Vik Paruchuri
4b01146865 Support different bbox format 2025-10-30 20:06:45 -04:00
Vik Paruchuri
7cf96f3911 Enable passing custom headers 2025-10-30 10:21:11 -04:00
Vik Paruchuri
607205211a Improve robustness 2025-10-29 18:16:40 -04:00
Vik Paruchuri
358358134e Fix lanczos 2025-10-26 10:38:04 -04:00
Vik Paruchuri
2d2d7ab331 Change image rendering 2025-10-26 10:27:49 -04:00
Vik Paruchuri
528b58c16f Track errors properly 2025-10-23 16:55:16 -04:00
Vik Paruchuri
5acfd8dc6a Patch image behavior 2025-10-23 12:19:41 -04:00
11 changed files with 195 additions and 61 deletions

View File

@@ -13,6 +13,15 @@ def flatten(page, flag=pdfium_c.FLAT_NORMALDISPLAY):
print(f"Failed to flatten annotations / form fields on page {page}.")
def load_image(filepath: str):
image = Image.open(filepath).convert("RGB")
if image.width < settings.MIN_IMAGE_DIM or image.height < settings.MIN_IMAGE_DIM:
scale = settings.MIN_IMAGE_DIM / min(image.width, image.height)
new_size = (int(image.width * scale), int(image.height * scale))
image = image.resize(new_size, Image.Resampling.LANCZOS)
return image
def load_pdf_images(filepath: str, page_range: List[int]):
doc = pdfium.PdfDocument(filepath)
doc.init_forms()
@@ -22,7 +31,7 @@ def load_pdf_images(filepath: str, page_range: List[int]):
if not page_range or page in page_range:
page_obj = doc[page]
min_page_dim = min(page_obj.get_width(), page_obj.get_height())
scale_dpi = (settings.MIN_IMAGE_DIM / min_page_dim) * 72
scale_dpi = (settings.MIN_PDF_IMAGE_DIM / min_page_dim) * 72
scale_dpi = max(scale_dpi, settings.IMAGE_DPI)
page_obj = doc[page]
flatten(page_obj)
@@ -56,5 +65,5 @@ def load_file(filepath: str, config: dict):
if input_type and input_type.extension == "pdf":
images = load_pdf_images(filepath, page_range)
else:
images = [Image.open(filepath).convert("RGB")]
images = [load_image(filepath)]
return images

View File

@@ -48,6 +48,7 @@ class InferenceManager:
page_box=[0, 0, input_item.image.width, input_item.image.height],
token_count=result.token_count,
images=extract_images(result.raw, chunks, input_item.image),
error=result.error,
)
)
return output

View File

@@ -5,6 +5,7 @@ from transformers import Qwen3VLForConditionalGeneration, Qwen3VLProcessor
from chandra.model.schema import BatchInputItem, GenerationResult
from chandra.model.util import scale_to_fit
from chandra.output import fix_raw
from chandra.prompts import PROMPT_MAPPING
from chandra.settings import settings
@@ -42,7 +43,7 @@ def generate_hf(
clean_up_tokenization_spaces=False,
)
results = [
GenerationResult(raw=out, token_count=len(ids), error=False)
GenerationResult(raw=fix_raw(out), token_count=len(ids), error=False)
for out, ids in zip(output_text, generated_ids_trimmed)
]
return results

View File

@@ -27,3 +27,4 @@ class BatchOutputItem:
page_box: List[int]
token_count: int
images: dict
error: bool

View File

@@ -44,9 +44,10 @@ def scale_to_fit(
def detect_repeat_token(
predicted_tokens: str,
max_repeats: int = 4,
base_max_repeats: int = 4,
window_size: int = 500,
cut_from_end: int = 0,
scaling_factor: float = 3.0,
):
try:
predicted_tokens = parse_markdown(predicted_tokens)
@@ -57,11 +58,13 @@ def detect_repeat_token(
if cut_from_end > 0:
predicted_tokens = predicted_tokens[:-cut_from_end]
# Try different sequence lengths (1 to window_size//2)
for seq_len in range(1, window_size // 2 + 1):
# Extract the potential repeating sequence from the end
candidate_seq = predicted_tokens[-seq_len:]
# Inverse scaling: shorter sequences need more repeats
max_repeats = int(base_max_repeats * (1 + scaling_factor / seq_len))
# Count how many times this sequence appears consecutively at the end
repeat_count = 0
pos = len(predicted_tokens) - seq_len
@@ -75,7 +78,6 @@ def detect_repeat_token(
else:
break
# If we found more than max_repeats consecutive occurrences
if repeat_count > max_repeats:
return True

View File

@@ -9,6 +9,7 @@ from openai import OpenAI
from chandra.model.schema import BatchInputItem, GenerationResult
from chandra.model.util import scale_to_fit, detect_repeat_token
from chandra.output import fix_raw
from chandra.prompts import PROMPT_MAPPING
from chandra.settings import settings
@@ -25,10 +26,12 @@ def generate_vllm(
max_output_tokens: int = None,
max_retries: int = None,
max_workers: int | None = None,
custom_headers: dict | None = None,
) -> List[GenerationResult]:
client = OpenAI(
api_key=settings.VLLM_API_KEY,
base_url=settings.VLLM_API_BASE,
default_headers=custom_headers,
)
model_name = settings.VLLM_MODEL_NAME
@@ -68,19 +71,22 @@ def generate_vllm(
completion = client.chat.completions.create(
model=model_name,
messages=[{"role": "user", "content": content}],
max_tokens=settings.MAX_OUTPUT_TOKENS,
max_tokens=max_output_tokens,
temperature=temperature,
top_p=top_p,
)
raw = completion.choices[0].message.content
raw = fix_raw(raw)
result = GenerationResult(
raw=raw,
token_count=completion.usage.completion_tokens,
error=False,
)
except Exception as e:
print(f"Error during VLLM generation: {e}")
return GenerationResult(raw="", token_count=0, error=True)
return GenerationResult(
raw=completion.choices[0].message.content,
token_count=completion.usage.completion_tokens,
error=False,
)
return result
def process_item(item, max_retries):
result = _generate(item)

View File

@@ -20,6 +20,15 @@ def get_image_name(html: str, div_idx: int):
return f"{html_hash}_{div_idx}_img.webp"
def fix_raw(html: str):
def replace_group(match):
numbers = re.findall(r"\d+", match.group(0))
return "[" + ",".join(numbers) + "]"
result = re.sub(r"(?:<BBOX\d+>){4}", replace_group, html)
return result
def extract_images(html: str, chunks: dict, image: Image.Image):
images = {}
div_idx = 0
@@ -30,7 +39,11 @@ def extract_images(html: str, chunks: dict, image: Image.Image):
if not img:
continue
bbox = chunk["bbox"]
block_image = image.crop(bbox)
try:
block_image = image.crop(bbox)
except ValueError:
# Happens when bbox coordinates are invalid
continue
img_name = get_image_name(html, div_idx)
images[img_name] = block_image
return images
@@ -67,6 +80,17 @@ def parse_html(
else:
img = BeautifulSoup(f"<img src='{img_src}'/>", "html.parser")
div.append(img)
# Wrap text content in <p> tags if no inner HTML tags exist
if label in ["Text"] and not re.search(
"<.+>", str(div.decode_contents()).strip()
):
# Add inner p tags if missing for text blocks
text_content = str(div.decode_contents()).strip()
text_content = f"<p>{text_content}</p>"
div.clear()
div.append(BeautifulSoup(text_content, "html.parser"))
content = str(div.decode_contents())
out_html += content
return out_html
@@ -213,10 +237,11 @@ def parse_layout(html: str, image: Image.Image):
layout_blocks = []
for div in top_level_divs:
bbox = div.get("data-bbox")
try:
bbox = json.loads(bbox)
except Exception:
bbox = [0, 0, 1, 1] # Fallback to a default bbox if parsing fails
bbox = [0, 0, 1, 1]
bbox = list(map(int, bbox))
# Normalize bbox

View File

@@ -143,6 +143,7 @@ def process():
"image_height": img_height,
"blocks": blocks_data,
"html": html_with_images,
"markdown": result.markdown,
}
)

View File

@@ -64,6 +64,20 @@
cursor: not-allowed;
}
.controls label {
display: flex;
align-items: center;
gap: 8px;
color: white;
font-size: 14px;
cursor: pointer;
user-select: none;
}
.controls input[type="checkbox"] {
cursor: pointer;
}
.loading {
display: none;
color: #f39c12;
@@ -75,6 +89,11 @@
font-weight: bold;
}
.success {
color: #27ae60;
font-weight: bold;
}
.screenshot-container {
display: none;
margin-top: 60px;
@@ -88,8 +107,18 @@
display: flex;
}
.left-panel, .right-panel {
flex: 1;
.left-panel {
flex: 0 0 40%;
display: flex;
flex-direction: column;
background: white;
border-radius: 8px;
overflow: hidden;
box-shadow: 0 4px 12px rgba(0,0,0,0.3);
}
.right-panel {
flex: 0 0 60%;
display: flex;
flex-direction: column;
background: white;
@@ -137,6 +166,7 @@
padding: 30px;
line-height: 1.6;
color: #333;
font-size: 24px;
}
.markdown-content h1, .markdown-content h2, .markdown-content h3 {
@@ -215,8 +245,14 @@
<input type="text" id="filePath" placeholder="Enter file path (e.g., /path/to/document.pdf)">
<input type="number" id="pageNumber" placeholder="Page" value="0" min="0">
<button id="processBtn" onclick="processFile()">Process</button>
<label>
<input type="checkbox" id="showLayoutBoxes" checked onchange="toggleLayoutBoxes()">
Show Layout Boxes
</label>
<button id="copyMarkdownBtn" onclick="copyMarkdown()" style="display: none;">Copy Markdown</button>
<span class="loading" id="loading">Processing...</span>
<span class="error" id="error"></span>
<span class="success" id="success"></span>
</div>
<div class="screenshot-container" id="container">
@@ -242,6 +278,11 @@
<script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/github-markdown-css/5.8.1/github-markdown.min.css" integrity="sha512-BrOPA520KmDMqieeM7XFe6a3u3Sb3F1JBaQnrIAmWg3EYrciJ+Qqe6ZcKCdfPv26rGcgTrJnZ/IdQEct8h3Zhw==" crossorigin="anonymous" referrerpolicy="no-referrer" />
<script>
// Global state to store markdown and canvas data
let currentMarkdown = null;
let currentData = null;
let currentImageSrc = null;
async function processFile() {
const filePath = document.getElementById('filePath').value;
const pageNumber = parseInt(document.getElementById('pageNumber').value) || 0;
@@ -285,6 +326,10 @@
}
function renderResults(data) {
// Store data for toggle functionality
currentData = data;
currentImageSrc = data.image_base64;
const canvas = document.getElementById('layoutCanvas');
const ctx = canvas.getContext('2d');
const markdownContent = document.getElementById('markdownContent');
@@ -292,51 +337,14 @@
// Draw image with layout overlays
const img = new Image();
img.onload = function() {
canvas.width = data.image_width;
canvas.height = data.image_height;
// Draw image
ctx.drawImage(img, 0, 0, data.image_width, data.image_height);
// Draw layout blocks
ctx.lineWidth = 3;
ctx.font = 'bold 14px -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif';
const labelCounts = {};
data.blocks.forEach((block) => {
const [x1, y1, x2, y2] = block.bbox;
const width = x2 - x1;
const height = y2 - y1;
// Draw rectangle with semi-transparent fill
ctx.strokeStyle = block.color;
ctx.fillStyle = block.color + '33';
ctx.fillRect(x1, y1, width, height);
ctx.strokeRect(x1, y1, width, height);
// Count labels for unique identification
labelCounts[block.label] = (labelCounts[block.label] || 0) + 1;
const labelWithCount = `${block.label} #${labelCounts[block.label]}`;
// Draw label with background
const textMetrics = ctx.measureText(labelWithCount);
const textWidth = textMetrics.width;
const textHeight = 16;
const padding = 6;
const labelX = x1;
const labelY = Math.max(y1 - textHeight - padding, textHeight);
ctx.fillStyle = block.color;
ctx.fillRect(labelX, labelY - textHeight, textWidth + padding * 2, textHeight + padding);
ctx.fillStyle = 'white';
ctx.textBaseline = 'top';
ctx.fillText(labelWithCount, labelX + padding, labelY - textHeight + padding/2);
});
drawCanvas(img, data, ctx);
};
img.src = data.image_base64;
// Store markdown and show copy button
currentMarkdown = data.markdown;
document.getElementById('copyMarkdownBtn').style.display = 'inline-block';
// Render HTML directly (with images embedded)
markdownContent.innerHTML = data.html;
@@ -362,6 +370,85 @@
});
}
function drawCanvas(img, data, ctx) {
const canvas = document.getElementById('layoutCanvas');
canvas.width = data.image_width;
canvas.height = data.image_height;
// Draw image
ctx.drawImage(img, 0, 0, data.image_width, data.image_height);
// Check if layout boxes should be shown
const showBoxes = document.getElementById('showLayoutBoxes').checked;
if (!showBoxes) return;
// Draw layout blocks
ctx.lineWidth = 3;
ctx.font = 'bold 14px -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif';
const labelCounts = {};
data.blocks.forEach((block) => {
const [x1, y1, x2, y2] = block.bbox;
const width = x2 - x1;
const height = y2 - y1;
// Draw rectangle with semi-transparent fill
ctx.strokeStyle = block.color;
ctx.fillStyle = block.color + '33';
ctx.fillRect(x1, y1, width, height);
ctx.strokeRect(x1, y1, width, height);
// Count labels for unique identification
labelCounts[block.label] = (labelCounts[block.label] || 0) + 1;
const labelWithCount = `${block.label} #${labelCounts[block.label]}`;
// Draw label with background
const textMetrics = ctx.measureText(labelWithCount);
const textWidth = textMetrics.width;
const textHeight = 16;
const padding = 6;
const labelX = x1;
const labelY = Math.max(y1 - textHeight - padding, textHeight);
ctx.fillStyle = block.color;
ctx.fillRect(labelX, labelY - textHeight, textWidth + padding * 2, textHeight + padding);
ctx.fillStyle = 'white';
ctx.textBaseline = 'top';
ctx.fillText(labelWithCount, labelX + padding, labelY - textHeight + padding/2);
});
}
function toggleLayoutBoxes() {
if (!currentData || !currentImageSrc) return;
const canvas = document.getElementById('layoutCanvas');
const ctx = canvas.getContext('2d');
const img = new Image();
img.onload = function() {
drawCanvas(img, currentData, ctx);
};
img.src = currentImageSrc;
}
function copyMarkdown() {
if (!currentMarkdown) {
document.getElementById('error').textContent = 'No markdown to copy';
return;
}
navigator.clipboard.writeText(currentMarkdown).then(() => {
const success = document.getElementById('success');
success.textContent = 'Markdown copied!';
setTimeout(() => {
success.textContent = '';
}, 2000);
}).catch((err) => {
document.getElementById('error').textContent = 'Failed to copy: ' + err.message;
});
}
// Allow Enter key to trigger processing
document.getElementById('filePath').addEventListener('keypress', function(e) {
if (e.key === 'Enter') processFile();

View File

@@ -9,10 +9,11 @@ class Settings(BaseSettings):
# Paths
BASE_DIR: str = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
IMAGE_DPI: int = 192
MIN_IMAGE_DIM: int = 1024
MIN_PDF_IMAGE_DIM: int = 1024
MIN_IMAGE_DIM: int = 1536
MODEL_CHECKPOINT: str = "datalab-to/chandra"
TORCH_DEVICE: str | None = None
MAX_OUTPUT_TOKENS: int = 8192
MAX_OUTPUT_TOKENS: int = 12384
TORCH_ATTN: str | None = None
# vLLM server settings

View File

@@ -1,6 +1,6 @@
[project]
name = "chandra-ocr"
version = "0.1.7"
version = "0.1.9"
description = "OCR model that converts documents to markdown, HTML, or JSON."
readme = "README.md"
requires-python = ">=3.10"