add: ocr_pipeline_overlays.py for overlay rendering functions
Extracted 4 overlay functions (_get_structure_overlay, _get_columns_overlay, _get_rows_overlay, _get_words_overlay) that were missing from the initial split. Provides render_overlay() dispatcher used by sessions module. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
547
klausur-service/backend/ocr_pipeline_overlays.py
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547
klausur-service/backend/ocr_pipeline_overlays.py
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"""
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Overlay image rendering for OCR pipeline.
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Generates visual overlays for structure, columns, rows, and words
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detection results.
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Lizenz: Apache 2.0
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DATENSCHUTZ: Alle Verarbeitung erfolgt lokal.
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"""
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import logging
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from dataclasses import asdict
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from typing import Any, Dict, List, Optional
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import cv2
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import numpy as np
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from fastapi import HTTPException
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from fastapi.responses import Response
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from ocr_pipeline_common import (
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_cache,
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_get_base_image_png,
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_load_session_to_cache,
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_get_cached,
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)
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from ocr_pipeline_session_store import get_session_db, get_session_image
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from cv_color_detect import _COLOR_HEX, _COLOR_RANGES
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from cv_box_detect import detect_boxes
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from ocr_pipeline_rows import _draw_box_exclusion_overlay
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logger = logging.getLogger(__name__)
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async def render_overlay(overlay_type: str, session_id: str) -> Response:
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"""Dispatch to the appropriate overlay renderer."""
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if overlay_type == "structure":
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return await _get_structure_overlay(session_id)
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elif overlay_type == "columns":
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return await _get_columns_overlay(session_id)
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elif overlay_type == "rows":
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return await _get_rows_overlay(session_id)
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elif overlay_type == "words":
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return await _get_words_overlay(session_id)
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else:
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raise HTTPException(status_code=400, detail=f"Unknown overlay type: {overlay_type}")
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async def _get_structure_overlay(session_id: str) -> Response:
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"""Generate overlay image showing detected boxes, zones, and color regions."""
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base_png = await _get_base_image_png(session_id)
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if not base_png:
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raise HTTPException(status_code=404, detail="No base image available")
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arr = np.frombuffer(base_png, dtype=np.uint8)
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img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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if img is None:
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raise HTTPException(status_code=500, detail="Failed to decode image")
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h, w = img.shape[:2]
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# Get structure result (run detection if not cached)
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session = await get_session_db(session_id)
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structure = (session or {}).get("structure_result")
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if not structure:
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# Run detection on-the-fly
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margin = int(min(w, h) * 0.03)
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content_x, content_y = margin, margin
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content_w_px = w - 2 * margin
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content_h_px = h - 2 * margin
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boxes = detect_boxes(img, content_x, content_w_px, content_y, content_h_px)
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zones = split_page_into_zones(content_x, content_y, content_w_px, content_h_px, boxes)
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structure = {
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"boxes": [
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{"x": b.x, "y": b.y, "w": b.width, "h": b.height,
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"confidence": b.confidence, "border_thickness": b.border_thickness}
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for b in boxes
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],
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"zones": [
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{"index": z.index, "zone_type": z.zone_type,
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"y": z.y, "h": z.height, "x": z.x, "w": z.width}
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for z in zones
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],
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}
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overlay = img.copy()
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# --- Draw zone boundaries ---
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zone_colors = {
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"content": (200, 200, 200), # light gray
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"box": (255, 180, 0), # blue-ish (BGR)
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}
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for zone in structure.get("zones", []):
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zx = zone["x"]
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zy = zone["y"]
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zw = zone["w"]
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zh = zone["h"]
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color = zone_colors.get(zone["zone_type"], (200, 200, 200))
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# Draw zone boundary as dashed line
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dash_len = 12
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for edge_x in range(zx, zx + zw, dash_len * 2):
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end_x = min(edge_x + dash_len, zx + zw)
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cv2.line(img, (edge_x, zy), (end_x, zy), color, 1)
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cv2.line(img, (edge_x, zy + zh), (end_x, zy + zh), color, 1)
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# Zone label
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zone_label = f"Zone {zone['index']} ({zone['zone_type']})"
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cv2.putText(img, zone_label, (zx + 5, zy + 15),
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cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 1)
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# --- Draw detected boxes ---
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# Color map for box backgrounds (BGR)
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bg_hex_to_bgr = {
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"#dc2626": (38, 38, 220), # red
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"#2563eb": (235, 99, 37), # blue
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"#16a34a": (74, 163, 22), # green
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"#ea580c": (12, 88, 234), # orange
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"#9333ea": (234, 51, 147), # purple
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"#ca8a04": (4, 138, 202), # yellow
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"#6b7280": (128, 114, 107), # gray
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}
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for box_data in structure.get("boxes", []):
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bx = box_data["x"]
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by = box_data["y"]
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bw = box_data["w"]
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bh = box_data["h"]
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conf = box_data.get("confidence", 0)
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thickness = box_data.get("border_thickness", 0)
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bg_hex = box_data.get("bg_color_hex", "#6b7280")
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bg_name = box_data.get("bg_color_name", "")
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# Box fill color
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fill_bgr = bg_hex_to_bgr.get(bg_hex, (128, 114, 107))
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# Semi-transparent fill
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cv2.rectangle(overlay, (bx, by), (bx + bw, by + bh), fill_bgr, -1)
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# Solid border
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border_color = fill_bgr
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cv2.rectangle(img, (bx, by), (bx + bw, by + bh), border_color, 3)
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# Label
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label = f"BOX"
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if bg_name and bg_name not in ("unknown", "white"):
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label += f" ({bg_name})"
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if thickness > 0:
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label += f" border={thickness}px"
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label += f" {int(conf * 100)}%"
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cv2.putText(img, label, (bx + 8, by + 22),
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cv2.FONT_HERSHEY_SIMPLEX, 0.55, (255, 255, 255), 2)
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cv2.putText(img, label, (bx + 8, by + 22),
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cv2.FONT_HERSHEY_SIMPLEX, 0.55, border_color, 1)
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# Blend overlay at 15% opacity
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cv2.addWeighted(overlay, 0.15, img, 0.85, 0, img)
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# --- Draw color regions (HSV masks) ---
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hsv = cv2.cvtColor(
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cv2.imdecode(np.frombuffer(base_png, dtype=np.uint8), cv2.IMREAD_COLOR),
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cv2.COLOR_BGR2HSV,
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)
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color_bgr_map = {
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"red": (0, 0, 255),
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"orange": (0, 140, 255),
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"yellow": (0, 200, 255),
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"green": (0, 200, 0),
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"blue": (255, 150, 0),
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"purple": (200, 0, 200),
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}
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for color_name, ranges in _COLOR_RANGES.items():
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mask = np.zeros((h, w), dtype=np.uint8)
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for lower, upper in ranges:
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mask = cv2.bitwise_or(mask, cv2.inRange(hsv, lower, upper))
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# Only draw if there are significant colored pixels
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if np.sum(mask > 0) < 100:
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continue
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# Draw colored contours
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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draw_color = color_bgr_map.get(color_name, (200, 200, 200))
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for cnt in contours:
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area = cv2.contourArea(cnt)
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if area < 20:
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continue
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cv2.drawContours(img, [cnt], -1, draw_color, 2)
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# --- Draw graphic elements ---
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graphics_data = structure.get("graphics", [])
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shape_icons = {
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"image": "IMAGE",
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"illustration": "ILLUST",
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}
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for gfx in graphics_data:
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gx, gy = gfx["x"], gfx["y"]
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gw, gh = gfx["w"], gfx["h"]
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shape = gfx.get("shape", "icon")
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color_hex = gfx.get("color_hex", "#6b7280")
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conf = gfx.get("confidence", 0)
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# Pick draw color based on element color (BGR)
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gfx_bgr = bg_hex_to_bgr.get(color_hex, (128, 114, 107))
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# Draw bounding box (dashed style via short segments)
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dash = 6
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for seg_x in range(gx, gx + gw, dash * 2):
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end_x = min(seg_x + dash, gx + gw)
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cv2.line(img, (seg_x, gy), (end_x, gy), gfx_bgr, 2)
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cv2.line(img, (seg_x, gy + gh), (end_x, gy + gh), gfx_bgr, 2)
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for seg_y in range(gy, gy + gh, dash * 2):
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end_y = min(seg_y + dash, gy + gh)
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cv2.line(img, (gx, seg_y), (gx, end_y), gfx_bgr, 2)
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cv2.line(img, (gx + gw, seg_y), (gx + gw, end_y), gfx_bgr, 2)
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# Label
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icon = shape_icons.get(shape, shape.upper()[:5])
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label = f"{icon} {int(conf * 100)}%"
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# White background for readability
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(tw, th), _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.4, 1)
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lx = gx + 2
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ly = max(gy - 4, th + 4)
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cv2.rectangle(img, (lx - 1, ly - th - 2), (lx + tw + 2, ly + 3), (255, 255, 255), -1)
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cv2.putText(img, label, (lx, ly), cv2.FONT_HERSHEY_SIMPLEX, 0.4, gfx_bgr, 1)
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# Encode result
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_, png_buf = cv2.imencode(".png", img)
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return Response(content=png_buf.tobytes(), media_type="image/png")
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async def _get_columns_overlay(session_id: str) -> Response:
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"""Generate cropped (or dewarped) image with column borders drawn on it."""
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session = await get_session_db(session_id)
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if not session:
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raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
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column_result = session.get("column_result")
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if not column_result or not column_result.get("columns"):
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raise HTTPException(status_code=404, detail="No column data available")
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# Load best available base image (cropped > dewarped > original)
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base_png = await _get_base_image_png(session_id)
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if not base_png:
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raise HTTPException(status_code=404, detail="No base image available")
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arr = np.frombuffer(base_png, dtype=np.uint8)
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img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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if img is None:
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raise HTTPException(status_code=500, detail="Failed to decode image")
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# Color map for region types (BGR)
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colors = {
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"column_en": (255, 180, 0), # Blue
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"column_de": (0, 200, 0), # Green
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"column_example": (0, 140, 255), # Orange
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"column_text": (200, 200, 0), # Cyan/Turquoise
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"page_ref": (200, 0, 200), # Purple
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"column_marker": (0, 0, 220), # Red
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"column_ignore": (180, 180, 180), # Light Gray
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"header": (128, 128, 128), # Gray
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"footer": (128, 128, 128), # Gray
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"margin_top": (100, 100, 100), # Dark Gray
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"margin_bottom": (100, 100, 100), # Dark Gray
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}
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overlay = img.copy()
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for col in column_result["columns"]:
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x, y = col["x"], col["y"]
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w, h = col["width"], col["height"]
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color = colors.get(col.get("type", ""), (200, 200, 200))
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# Semi-transparent fill
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cv2.rectangle(overlay, (x, y), (x + w, y + h), color, -1)
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# Solid border
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cv2.rectangle(img, (x, y), (x + w, y + h), color, 3)
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# Label with confidence
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label = col.get("type", "unknown").replace("column_", "").upper()
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conf = col.get("classification_confidence")
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if conf is not None and conf < 1.0:
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label = f"{label} {int(conf * 100)}%"
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cv2.putText(img, label, (x + 10, y + 30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, color, 2)
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# Blend overlay at 20% opacity
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cv2.addWeighted(overlay, 0.2, img, 0.8, 0, img)
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# Draw detected box boundaries as dashed rectangles
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zones = column_result.get("zones") or []
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for zone in zones:
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if zone.get("zone_type") == "box" and zone.get("box"):
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box = zone["box"]
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bx, by = box["x"], box["y"]
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bw, bh = box["width"], box["height"]
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box_color = (0, 200, 255) # Yellow (BGR)
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# Draw dashed rectangle by drawing short line segments
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dash_len = 15
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for edge_x in range(bx, bx + bw, dash_len * 2):
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end_x = min(edge_x + dash_len, bx + bw)
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cv2.line(img, (edge_x, by), (end_x, by), box_color, 2)
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cv2.line(img, (edge_x, by + bh), (end_x, by + bh), box_color, 2)
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for edge_y in range(by, by + bh, dash_len * 2):
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end_y = min(edge_y + dash_len, by + bh)
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cv2.line(img, (bx, edge_y), (bx, end_y), box_color, 2)
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cv2.line(img, (bx + bw, edge_y), (bx + bw, end_y), box_color, 2)
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cv2.putText(img, "BOX", (bx + 10, by + bh - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, box_color, 2)
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# Red semi-transparent overlay for box zones
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_draw_box_exclusion_overlay(img, zones)
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success, result_png = cv2.imencode(".png", img)
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if not success:
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raise HTTPException(status_code=500, detail="Failed to encode overlay image")
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return Response(content=result_png.tobytes(), media_type="image/png")
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# ---------------------------------------------------------------------------
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# Row Detection Endpoints
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# ---------------------------------------------------------------------------
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async def _get_rows_overlay(session_id: str) -> Response:
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"""Generate cropped (or dewarped) image with row bands drawn on it."""
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session = await get_session_db(session_id)
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if not session:
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raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
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row_result = session.get("row_result")
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if not row_result or not row_result.get("rows"):
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raise HTTPException(status_code=404, detail="No row data available")
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# Load best available base image (cropped > dewarped > original)
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base_png = await _get_base_image_png(session_id)
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if not base_png:
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raise HTTPException(status_code=404, detail="No base image available")
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arr = np.frombuffer(base_png, dtype=np.uint8)
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img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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if img is None:
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raise HTTPException(status_code=500, detail="Failed to decode image")
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# Color map for row types (BGR)
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row_colors = {
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"content": (255, 180, 0), # Blue
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"header": (128, 128, 128), # Gray
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"footer": (128, 128, 128), # Gray
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"margin_top": (100, 100, 100), # Dark Gray
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"margin_bottom": (100, 100, 100), # Dark Gray
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}
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overlay = img.copy()
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for row in row_result["rows"]:
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x, y = row["x"], row["y"]
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w, h = row["width"], row["height"]
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row_type = row.get("row_type", "content")
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color = row_colors.get(row_type, (200, 200, 200))
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# Semi-transparent fill
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cv2.rectangle(overlay, (x, y), (x + w, y + h), color, -1)
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# Solid border
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cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
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# Label
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idx = row.get("index", 0)
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label = f"R{idx} {row_type.upper()}"
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wc = row.get("word_count", 0)
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if wc:
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label = f"{label} ({wc}w)"
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cv2.putText(img, label, (x + 5, y + 18),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1)
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# Blend overlay at 15% opacity
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cv2.addWeighted(overlay, 0.15, img, 0.85, 0, img)
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# Draw zone separator lines if zones exist
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column_result = session.get("column_result") or {}
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zones = column_result.get("zones") or []
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if zones:
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img_w_px = img.shape[1]
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zone_color = (0, 200, 255) # Yellow (BGR)
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dash_len = 20
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for zone in zones:
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if zone.get("zone_type") == "box":
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zy = zone["y"]
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zh = zone["height"]
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for line_y in [zy, zy + zh]:
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for sx in range(0, img_w_px, dash_len * 2):
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ex = min(sx + dash_len, img_w_px)
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cv2.line(img, (sx, line_y), (ex, line_y), zone_color, 2)
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# Red semi-transparent overlay for box zones
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_draw_box_exclusion_overlay(img, zones)
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success, result_png = cv2.imencode(".png", img)
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if not success:
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raise HTTPException(status_code=500, detail="Failed to encode overlay image")
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return Response(content=result_png.tobytes(), media_type="image/png")
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|
||||
async def _get_words_overlay(session_id: str) -> Response:
|
||||
"""Generate cropped (or dewarped) image with cell grid drawn on it."""
|
||||
session = await get_session_db(session_id)
|
||||
if not session:
|
||||
raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
|
||||
|
||||
word_result = session.get("word_result")
|
||||
if not word_result:
|
||||
raise HTTPException(status_code=404, detail="No word data available")
|
||||
|
||||
# Support both new cell-based and legacy entry-based formats
|
||||
cells = word_result.get("cells")
|
||||
if not cells and not word_result.get("entries"):
|
||||
raise HTTPException(status_code=404, detail="No word data available")
|
||||
|
||||
# Load best available base image (cropped > dewarped > original)
|
||||
base_png = await _get_base_image_png(session_id)
|
||||
if not base_png:
|
||||
raise HTTPException(status_code=404, detail="No base image available")
|
||||
|
||||
arr = np.frombuffer(base_png, dtype=np.uint8)
|
||||
img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
|
||||
if img is None:
|
||||
raise HTTPException(status_code=500, detail="Failed to decode image")
|
||||
|
||||
img_h, img_w = img.shape[:2]
|
||||
|
||||
overlay = img.copy()
|
||||
|
||||
if cells:
|
||||
# New cell-based overlay: color by column index
|
||||
col_palette = [
|
||||
(255, 180, 0), # Blue (BGR)
|
||||
(0, 200, 0), # Green
|
||||
(0, 140, 255), # Orange
|
||||
(200, 100, 200), # Purple
|
||||
(200, 200, 0), # Cyan
|
||||
(100, 200, 200), # Yellow-ish
|
||||
]
|
||||
|
||||
for cell in cells:
|
||||
bbox = cell.get("bbox_px", {})
|
||||
cx = bbox.get("x", 0)
|
||||
cy = bbox.get("y", 0)
|
||||
cw = bbox.get("w", 0)
|
||||
ch = bbox.get("h", 0)
|
||||
if cw <= 0 or ch <= 0:
|
||||
continue
|
||||
|
||||
col_idx = cell.get("col_index", 0)
|
||||
color = col_palette[col_idx % len(col_palette)]
|
||||
|
||||
# Cell rectangle border
|
||||
cv2.rectangle(img, (cx, cy), (cx + cw, cy + ch), color, 1)
|
||||
# Semi-transparent fill
|
||||
cv2.rectangle(overlay, (cx, cy), (cx + cw, cy + ch), color, -1)
|
||||
|
||||
# Cell-ID label (top-left corner)
|
||||
cell_id = cell.get("cell_id", "")
|
||||
cv2.putText(img, cell_id, (cx + 2, cy + 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 0.28, color, 1)
|
||||
|
||||
# Text label (bottom of cell)
|
||||
text = cell.get("text", "")
|
||||
if text:
|
||||
conf = cell.get("confidence", 0)
|
||||
if conf >= 70:
|
||||
text_color = (0, 180, 0)
|
||||
elif conf >= 50:
|
||||
text_color = (0, 180, 220)
|
||||
else:
|
||||
text_color = (0, 0, 220)
|
||||
|
||||
label = text.replace('\n', ' ')[:30]
|
||||
cv2.putText(img, label, (cx + 3, cy + ch - 4),
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 0.35, text_color, 1)
|
||||
else:
|
||||
# Legacy fallback: entry-based overlay (for old sessions)
|
||||
column_result = session.get("column_result")
|
||||
row_result = session.get("row_result")
|
||||
col_colors = {
|
||||
"column_en": (255, 180, 0),
|
||||
"column_de": (0, 200, 0),
|
||||
"column_example": (0, 140, 255),
|
||||
}
|
||||
|
||||
columns = []
|
||||
if column_result and column_result.get("columns"):
|
||||
columns = [c for c in column_result["columns"]
|
||||
if c.get("type", "").startswith("column_")]
|
||||
|
||||
content_rows_data = []
|
||||
if row_result and row_result.get("rows"):
|
||||
content_rows_data = [r for r in row_result["rows"]
|
||||
if r.get("row_type") == "content"]
|
||||
|
||||
for col in columns:
|
||||
col_type = col.get("type", "")
|
||||
color = col_colors.get(col_type, (200, 200, 200))
|
||||
cx, cw = col["x"], col["width"]
|
||||
for row in content_rows_data:
|
||||
ry, rh = row["y"], row["height"]
|
||||
cv2.rectangle(img, (cx, ry), (cx + cw, ry + rh), color, 1)
|
||||
cv2.rectangle(overlay, (cx, ry), (cx + cw, ry + rh), color, -1)
|
||||
|
||||
entries = word_result["entries"]
|
||||
entry_by_row: Dict[int, Dict] = {}
|
||||
for entry in entries:
|
||||
entry_by_row[entry.get("row_index", -1)] = entry
|
||||
|
||||
for row_idx, row in enumerate(content_rows_data):
|
||||
entry = entry_by_row.get(row_idx)
|
||||
if not entry:
|
||||
continue
|
||||
conf = entry.get("confidence", 0)
|
||||
text_color = (0, 180, 0) if conf >= 70 else (0, 180, 220) if conf >= 50 else (0, 0, 220)
|
||||
ry, rh = row["y"], row["height"]
|
||||
for col in columns:
|
||||
col_type = col.get("type", "")
|
||||
cx, cw = col["x"], col["width"]
|
||||
field = {"column_en": "english", "column_de": "german", "column_example": "example"}.get(col_type, "")
|
||||
text = entry.get(field, "") if field else ""
|
||||
if text:
|
||||
label = text.replace('\n', ' ')[:30]
|
||||
cv2.putText(img, label, (cx + 3, ry + rh - 4),
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 0.35, text_color, 1)
|
||||
|
||||
# Blend overlay at 10% opacity
|
||||
cv2.addWeighted(overlay, 0.1, img, 0.9, 0, img)
|
||||
|
||||
# Red semi-transparent overlay for box zones
|
||||
column_result = session.get("column_result") or {}
|
||||
zones = column_result.get("zones") or []
|
||||
_draw_box_exclusion_overlay(img, zones)
|
||||
|
||||
success, result_png = cv2.imencode(".png", img)
|
||||
if not success:
|
||||
raise HTTPException(status_code=500, detail="Failed to encode overlay image")
|
||||
|
||||
return Response(content=result_png.tobytes(), media_type="image/png")
|
||||
|
||||
Reference in New Issue
Block a user