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Renders a unified clinical dashboard PNG that nurses and clinicians can review
at a glance. Combines:
- Original photograph
- Binary ulcer mask
- Multi-class tissue map (background / foot / perilesion / ulcer)
- Class area distribution (horizontal bars)
- Fitzpatrick / ITA estimation with color-coded badge
- PWAT items 3-8 table (raw vs adjusted, delta, severity bars)
- Total raw / total adjusted + clinical interpretation by range
- Lighting-quality warnings when applicable
Designed for clinical staff: clean typography, clear hierarchy, consistent
palette, fixed 1920x1200 px layout.
Usage:
from src.integrated_report import render_integrated_report
dashboard = render_integrated_report(rgb, binary_overlay, multi_overlay, result)
# dashboard: np.ndarray RGB (1200, 1920, 3) uint8
"""
from __future__ import annotations
from datetime import datetime
import cv2
import numpy as np
from PIL import Image, ImageDraw, ImageFont
from src.pwat_estimator import ITEM_NAMES
# ββ Palette and design constants ββββββββββββββββββββββββββββββββββββββββββββ
DASH_W, DASH_H = 1920, 1200
COL_BG = (248, 250, 252) # slate-50
COL_CARD = (255, 255, 255)
COL_CARD_BORDER = (226, 232, 240) # slate-200
COL_INK = (15, 23, 42) # slate-900
COL_INK_SOFT = (71, 85, 105) # slate-600
COL_INK_MUTE = (148, 163, 184) # slate-400
COL_HEADER_BG = (15, 23, 42)
COL_HEADER_FG = (248, 250, 252)
COL_ACCENT = (14, 116, 144) # cyan-700
COL_DANGER = (220, 38, 38) # red-600
COL_WARN = (217, 119, 6) # amber-600
COL_OK = (5, 150, 105) # emerald-600
COL_INFO = (37, 99, 235) # blue-600
CLASS_COLOR = {
"foot": (34, 197, 94), # green-500
"perilesion": (249, 115, 22), # orange-500
"ulcer": (239, 68, 68), # red-500
"background": (107, 114, 128), # gray-500
}
CLASS_LABEL_EN = {
"foot": "Healthy foot",
"perilesion": "Perilesional",
"ulcer": "Ulcer",
"background": "Background",
}
FITZ_RGB = {
"I": (254, 243, 199),
"II": (253, 224, 138),
"III": (245, 158, 11),
"IV": (180, 83, 9),
"V": (120, 53, 15),
"VI": (45, 16, 4),
}
FITZ_TEXT_RGB = {
"I": (31, 41, 55), "II": (31, 41, 55), "III": (31, 41, 55),
"IV": (255, 255, 255), "V": (255, 255, 255), "VI": (255, 255, 255),
}
PWAT_INTERPRETATION = [
(0, 6, "Healing well", COL_OK),
(7, 12, "Moderate compromise β clinical follow-up", COL_WARN),
(13, 18, "Severe compromise β adjust treatment", COL_DANGER),
(19, 24, "Critical β urgent reassessment", (153, 27, 27)),
]
SEV_LABEL = {0: "Normal", 1: "Mild", 2: "Moderate", 3: "Severe", 4: "Extreme"}
# ββ Font helpers βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_FONT_BOLD_CANDIDATES = [
"DejaVuSans-Bold.ttf",
"C:/Windows/Fonts/segoeuib.ttf",
"C:/Windows/Fonts/arialbd.ttf",
"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
"/System/Library/Fonts/Supplemental/Arial Bold.ttf",
]
_FONT_REG_CANDIDATES = [
"DejaVuSans.ttf",
"C:/Windows/Fonts/segoeui.ttf",
"C:/Windows/Fonts/arial.ttf",
"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
"/System/Library/Fonts/Supplemental/Arial.ttf",
]
def _load_font(candidates, size):
for path in candidates:
try:
return ImageFont.truetype(path, size)
except (OSError, IOError):
continue
return ImageFont.load_default()
def _font_b(size: int):
return _load_font(_FONT_BOLD_CANDIDATES, size)
def _font_r(size: int):
return _load_font(_FONT_REG_CANDIDATES, size)
def _text_size(draw: ImageDraw.ImageDraw, text: str, font) -> tuple[int, int]:
box = draw.textbbox((0, 0), text, font=font)
return box[2] - box[0], box[3] - box[1]
# ββ Drawing helpers ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def _rounded_card(draw: ImageDraw.ImageDraw, xy, radius=14,
fill=COL_CARD, border=COL_CARD_BORDER, border_w=1,
shadow=True):
"""Rounded card with subtle drop shadow."""
x1, y1, x2, y2 = xy
if shadow:
for off, alpha in [(2, 18), (4, 8)]:
shadow_color = (15, 23, 42, alpha)
draw.rounded_rectangle(
(x1 + off, y1 + off, x2 + off, y2 + off),
radius=radius, fill=shadow_color,
)
draw.rounded_rectangle((x1, y1, x2, y2), radius=radius,
fill=fill, outline=border, width=border_w)
def _fit_image_into(img_rgb: np.ndarray, w: int, h: int) -> np.ndarray:
"""Letterbox an image into a w x h canvas preserving aspect ratio."""
if img_rgb is None or img_rgb.size == 0:
return np.full((h, w, 3), 240, dtype=np.uint8)
src_h, src_w = img_rgb.shape[:2]
scale = min(w / src_w, h / src_h)
new_w, new_h = int(src_w * scale), int(src_h * scale)
resized = cv2.resize(img_rgb, (new_w, new_h), interpolation=cv2.INTER_AREA)
canvas = np.full((h, w, 3), 245, dtype=np.uint8)
off_x = (w - new_w) // 2
off_y = (h - new_h) // 2
canvas[off_y:off_y + new_h, off_x:off_x + new_w] = resized
return canvas
def _paste_image(base_img: Image.Image, np_rgb: np.ndarray, box: tuple[int, int, int, int]):
x1, y1, x2, y2 = box
fitted = _fit_image_into(np_rgb, x2 - x1, y2 - y1)
base_img.paste(Image.fromarray(fitted), (x1, y1))
def _hbar(draw, x, y, w, h, value, vmax, color, bg=(229, 231, 235), radius=4):
"""Rounded horizontal bar with proportional fill."""
draw.rounded_rectangle((x, y, x + w, y + h), radius=radius, fill=bg)
if vmax > 0 and value > 0:
fill_w = max(2, int(w * value / vmax))
draw.rounded_rectangle((x, y, x + fill_w, y + h), radius=radius, fill=color)
def _interpretation_for(total: float) -> tuple[str, tuple]:
"""Map a (possibly fractional) PWAT total to its clinical band.
Rounds to nearest integer first so that 6.7 falls into the 7-12 band
(matches how clinicians read these cutoffs).
"""
rounded = int(round(max(0.0, min(24.0, total))))
for lo, hi, label, color in PWAT_INTERPRETATION:
if lo <= rounded <= hi:
return label, color
return PWAT_INTERPRETATION[-1][2], PWAT_INTERPRETATION[-1][3]
def _draw_wrapped_text(draw, text, xy, max_w, font, fill, max_lines=3):
"""Simple word-wrap by pixel width."""
if not text:
return
words = text.split()
lines, cur = [], ""
for w in words:
trial = (cur + " " + w).strip()
tw, _ = _text_size(draw, trial, font)
if tw <= max_w:
cur = trial
else:
if cur:
lines.append(cur)
cur = w
if len(lines) >= max_lines:
break
if cur and len(lines) < max_lines:
lines.append(cur)
if len(lines) == max_lines and len(" ".join(lines)) < len(text):
last = lines[-1]
while last and _text_size(draw, last + "...", font)[0] > max_w:
last = last[:-1]
lines[-1] = last + "..."
x, y = xy
line_h = font.size + 4 if hasattr(font, "size") else 18
for ln in lines:
draw.text((x, y), ln, fill=fill, font=font)
y += line_h
# ββ Dashboard blocks βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def _draw_header(img: Image.Image, draw: ImageDraw.ImageDraw):
H = 90
draw.rectangle((0, 0, DASH_W, H), fill=COL_HEADER_BG)
# Logo accent
dot_x, dot_y = 36, 32
draw.ellipse((dot_x, dot_y, dot_x + 26, dot_y + 26), fill=(34, 197, 94))
draw.ellipse((dot_x + 6, dot_y + 6, dot_x + 20, dot_y + 20), fill=COL_HEADER_BG)
title = "Integrated Diabetic Foot Ulcer Assessment Report"
subtitle = ("WoundNetB7 - EfficientNet-B7 + ASPP + CBAM + CoordAttention + TAM "
" - Ulcer Dice 0.927")
draw.text((78, 18), title, fill=COL_HEADER_FG, font=_font_b(28))
draw.text((78, 56), subtitle, fill=(148, 163, 184), font=_font_r(15))
# Right-side timestamp + advisory
ts = datetime.now().strftime("%Y-%m-%d %H:%M")
ts_w, _ = _text_size(draw, ts, _font_r(15))
draw.text((DASH_W - 36 - ts_w, 22), ts, fill=(148, 163, 184), font=_font_r(15))
advisory = "Research use only β not a clinical diagnosis"
adv_w, _ = _text_size(draw, advisory, _font_r(13))
draw.text((DASH_W - 36 - adv_w, 46), advisory, fill=(251, 191, 36), font=_font_r(13))
def _draw_image_strip(img: Image.Image, draw: ImageDraw.ImageDraw,
original_rgb, binary_rgb, multi_rgb, class_distribution: dict):
"""Top row: original + binary + multiclass + class distribution."""
y0 = 110
y1 = y0 + 360
pad = 20
card_w = (DASH_W - pad * 5) // 4
titles = ["Original Image", "Binary Ulcer Mask",
"Multi-Class Segmentation", "Class Area Distribution"]
images = [original_rgb, binary_rgb, multi_rgb, None]
for i, (t, im) in enumerate(zip(titles, images)):
x1 = pad + i * (card_w + pad)
x2 = x1 + card_w
_rounded_card(draw, (x1, y0, x2, y1))
draw.text((x1 + 16, y0 + 12), t, fill=COL_INK, font=_font_b(15))
cx1, cy1, cx2, cy2 = x1 + 14, y0 + 42, x2 - 14, y1 - 14
if im is not None:
_paste_image(img, im, (cx1, cy1, cx2, cy2))
else:
_draw_class_distribution(draw, class_distribution, (cx1, cy1, cx2, cy2))
def _draw_class_distribution(draw, dist: dict, box: tuple[int, int, int, int]):
x1, y1, x2, y2 = box
inner_w = x2 - x1
items = [("ulcer", dist.get("ulcer", 0)),
("perilesion", dist.get("perilesion", 0)),
("foot", dist.get("foot", 0)),
("background", dist.get("background", 0))]
row_h = 56
cur_y = y1 + 6
for cls, pct in items:
color = CLASS_COLOR[cls]
label = CLASS_LABEL_EN[cls]
draw.rounded_rectangle((x1, cur_y, x1 + 14, cur_y + 14), radius=3, fill=color)
draw.text((x1 + 24, cur_y - 2), label, fill=COL_INK, font=_font_b(15))
pct_text = f"{pct:.1f} %"
pw, _ = _text_size(draw, pct_text, _font_b(15))
draw.text((x2 - pw, cur_y - 2), pct_text, fill=COL_INK, font=_font_b(15))
_hbar(draw, x1, cur_y + 22, inner_w, 10,
value=min(pct, 100), vmax=100, color=color,
bg=(241, 245, 249), radius=5)
cur_y += row_h
def _draw_fitzpatrick_card(draw: ImageDraw.ImageDraw, fitz, x1: int, y1: int, x2: int, y2: int):
"""Fitzpatrick / ITA card."""
_rounded_card(draw, (x1, y1, x2, y2))
draw.text((x1 + 22, y1 + 14),
"Fitzpatrick / ITA Skin Type Estimation",
fill=COL_INK, font=_font_b(18))
draw.text((x1 + 22, y1 + 42),
"Calibrated on 61 DFU images β 86.9% exact match β r=0.975",
fill=COL_INK_SOFT, font=_font_r(13))
if fitz is None or getattr(fitz, "confidence", 0) == 0:
draw.text((x1 + 22, y1 + 80),
"Not estimable (insufficient healthy-skin pixels).",
fill=COL_INK_MUTE, font=_font_r(15))
return
ftype = fitz.fitzpatrick_type
bg_c = FITZ_RGB.get(ftype, (229, 231, 235))
fg_c = FITZ_TEXT_RGB.get(ftype, COL_INK)
light_q = getattr(fitz, "lighting_quality", "good")
light_warn = getattr(fitz, "lighting_warning", "")
banner_y = y1 + 70
banner_h = 0
if light_q == "insufficient":
banner_h = 56
draw.rounded_rectangle((x1 + 22, banner_y, x2 - 22, banner_y + banner_h),
radius=8, fill=(254, 242, 242),
outline=(252, 165, 165), width=1)
draw.text((x1 + 36, banner_y + 8), "Insufficient lighting",
fill=(185, 28, 28), font=_font_b(14))
_draw_wrapped_text(draw, light_warn,
(x1 + 36, banner_y + 28), x2 - 22 - 36,
_font_r(12), (153, 27, 27), max_lines=2)
elif light_q == "low":
banner_h = 56
draw.rounded_rectangle((x1 + 22, banner_y, x2 - 22, banner_y + banner_h),
radius=8, fill=(255, 251, 235),
outline=(252, 211, 77), width=1)
draw.text((x1 + 36, banner_y + 8), "Suboptimal lighting",
fill=(180, 83, 9), font=_font_b(14))
_draw_wrapped_text(draw, light_warn,
(x1 + 36, banner_y + 28), x2 - 22 - 36,
_font_r(12), (146, 64, 14), max_lines=2)
body_y = y1 + 82 + banner_h
# Skin-tone badge
badge_w, badge_h = 220, 220
bx1, by1 = x1 + 22, body_y
bx2, by2 = bx1 + badge_w, by1 + badge_h
draw.rounded_rectangle((bx1, by1, bx2, by2), radius=18,
fill=bg_c, outline=(180, 180, 180), width=2)
draw.text((bx1 + 24, by1 + 32), "TYPE", fill=fg_c, font=_font_b(20))
big = _font_b(110)
bw, _ = _text_size(draw, ftype, big)
draw.text((bx1 + (badge_w - bw) // 2, by1 + 60), ftype, fill=fg_c, font=big)
label_font = _font_r(18)
lw, _ = _text_size(draw, fitz.fitzpatrick_label, label_font)
draw.text((bx1 + (badge_w - lw) // 2, by2 - 36),
fitz.fitzpatrick_label, fill=fg_c, font=label_font)
# Detail rows on the right
dx = bx2 + 30
dy = by1 + 6
rows = [
("ITA", f"{fitz.ita_angle:.1f} +/- {fitz.ita_std:.1f} deg"),
("L* healthy skin", f"{fitz.l_skin_mean:.1f}"),
("L* scene (global)", f"{getattr(fitz, 'l_scene_mean', 0):.1f}"),
("b* healthy skin", f"{fitz.b_skin_mean:.1f}"),
("Healthy pixels", f"{fitz.healthy_pixels:,}"),
("Confidence", f"{fitz.confidence:.0%}"),
]
for k, v in rows:
draw.text((dx, dy), k + ":", fill=COL_INK_SOFT, font=_font_r(14))
draw.text((dx + 170, dy), v, fill=COL_INK, font=_font_b(14))
dy += 28
# Confidence bar
cy = by2 - 22
_hbar(draw, dx, cy, x2 - 30 - dx, 8,
value=fitz.confidence, vmax=1.0,
color=COL_OK if fitz.confidence > 0.6
else (COL_WARN if fitz.confidence > 0.3 else COL_DANGER),
bg=(241, 245, 249))
def _draw_pwat_card(draw: ImageDraw.ImageDraw, pwat, x1: int, y1: int, x2: int, y2: int):
"""PWAT card: raw vs adjusted table + totals + interpretation."""
_rounded_card(draw, (x1, y1, x2, y2))
draw.text((x1 + 22, y1 + 14),
"PWAT Score (raw vs Fitzpatrick-adjusted)",
fill=COL_INK, font=_font_b(18))
fitz_label = pwat.fitzpatrick_type if pwat else "-"
sub = (f"Items 3-8 β 0-4 ordinal scale per item β "
f"calibrated correction for Fitzpatrick {fitz_label}")
draw.text((x1 + 22, y1 + 42), sub, fill=COL_INK_SOFT, font=_font_r(13))
if pwat is None or not pwat.scores_raw:
draw.text((x1 + 22, y1 + 90),
"Not estimable (ulcer not detected or area too small).",
fill=COL_INK_MUTE, font=_font_r(15))
return
table_x = x1 + 22
table_w = (x2 - x1) - 44
table_y = y1 + 78
col_label_w = 200
col_raw_w = 90
col_adj_w = 110
col_delta_w = 80
col_bar_w = 100
col_sev_w = table_w - col_label_w - col_raw_w - col_adj_w - col_delta_w - col_bar_w
# Header row
draw.rectangle((table_x, table_y, table_x + table_w, table_y + 28),
fill=(241, 245, 249))
cx = table_x + 12
headers = [
("PWAT Item", col_label_w),
("Raw", col_raw_w),
("Adjusted", col_adj_w),
("Delta", col_delta_w),
("Severity", col_bar_w),
("Interpretation", col_sev_w),
]
for h, w in headers:
draw.text((cx, table_y + 6), h, fill=COL_INK_SOFT, font=_font_b(13))
cx += w
row_y = table_y + 32
row_h = 38
for item in [3, 4, 5, 6, 7, 8]:
name = ITEM_NAMES.get(item, f"Item {item}")
raw = pwat.scores_raw.get(item, 0)
adj = pwat.scores_adjusted.get(item, 0.0)
delta = adj - raw
cx = table_x + 12
if (item % 2) == 0:
draw.rectangle((table_x, row_y - 4, table_x + table_w, row_y + row_h - 4),
fill=(248, 250, 252))
draw.text((cx, row_y + 4), name, fill=COL_INK, font=_font_b(14))
cx += col_label_w
draw.text((cx, row_y + 4), str(raw), fill=COL_INK, font=_font_b(15))
cx += col_raw_w
draw.text((cx, row_y + 4), f"{adj:.1f}", fill=COL_ACCENT, font=_font_b(15))
cx += col_adj_w
if abs(delta) < 0.05:
d_txt = "0.0"
d_col = COL_INK_SOFT
else:
d_txt = f"{delta:+.1f}"
d_col = COL_OK if delta < 0 else COL_DANGER
draw.text((cx, row_y + 4), d_txt, fill=d_col, font=_font_b(15))
cx += col_delta_w
_hbar(draw, cx, row_y + 10, col_bar_w - 14, 12,
value=raw, vmax=4, color=COL_DANGER, bg=(229, 231, 235), radius=6)
cx += col_bar_w
draw.text((cx, row_y + 4), SEV_LABEL.get(raw, ""),
fill=COL_INK_SOFT, font=_font_r(13))
draw.line((table_x, row_y + row_h - 4, table_x + table_w, row_y + row_h - 4),
fill=(241, 245, 249), width=1)
row_y += row_h
# Totals block
totals_y = row_y + 10
totals_h = 110
block_x1 = table_x
block_x2 = table_x + table_w
draw.rounded_rectangle((block_x1, totals_y, block_x2, totals_y + totals_h),
radius=10, fill=(15, 23, 42))
label, color = _interpretation_for(pwat.total_adjusted)
# Total raw
draw.text((block_x1 + 24, totals_y + 14),
"Total Raw", fill=(148, 163, 184), font=_font_r(13))
draw.text((block_x1 + 24, totals_y + 32),
str(pwat.total_raw), fill=COL_HEADER_FG, font=_font_b(36))
draw.text((block_x1 + 24, totals_y + 76),
"/ 24", fill=(100, 116, 139), font=_font_r(13))
# Total adjusted
draw.text((block_x1 + 180, totals_y + 14),
"Total Adjusted", fill=(148, 163, 184), font=_font_r(13))
draw.text((block_x1 + 180, totals_y + 30),
f"{pwat.total_adjusted:.1f}", fill=color, font=_font_b(44))
delta_total = pwat.total_adjusted - pwat.total_raw
if abs(delta_total) >= 0.05:
draw.text((block_x1 + 180, totals_y + 84),
f"({delta_total:+.1f} bias correction)",
fill=(148, 163, 184), font=_font_r(13))
# Clinical interpretation
interp_x = block_x1 + 410
draw.text((interp_x, totals_y + 14),
"Clinical Interpretation", fill=(148, 163, 184), font=_font_r(13))
draw.text((interp_x, totals_y + 32),
label, fill=color, font=_font_b(20))
# Mini gradient bar with marker
seg_x = interp_x
seg_y = totals_y + 70
seg_w = block_x2 - seg_x - 24
seg_h = 14
draw.rounded_rectangle((seg_x, seg_y, seg_x + seg_w, seg_y + seg_h),
radius=4, fill=(30, 41, 59))
seg_total = 24
cur_x = seg_x
for lo, hi, _, c in PWAT_INTERPRETATION:
seg_len = int(seg_w * (hi - lo + 1) / seg_total)
draw.rectangle((cur_x, seg_y, cur_x + seg_len, seg_y + seg_h), fill=c)
cur_x += seg_len
pos = seg_x + int(seg_w * pwat.total_adjusted / seg_total)
draw.polygon([
(pos - 6, seg_y - 4),
(pos + 6, seg_y - 4),
(pos, seg_y + 2),
], fill=COL_HEADER_FG)
tick_font = _font_r(11)
draw.text((seg_x, seg_y + seg_h + 4), "0",
fill=(148, 163, 184), font=tick_font)
draw.text((seg_x + seg_w - 14, seg_y + seg_h + 4), "24",
fill=(148, 163, 184), font=tick_font)
def _draw_footer(draw: ImageDraw.ImageDraw):
y = DASH_H - 32
draw.line((0, y - 8, DASH_W, y - 8), fill=(226, 232, 240), width=1)
txt = ("WoundNetB7 β Doctoral Thesis β Marcelo Marquez-Murillo | "
"Dice 0.927 (95% CI 0.917-0.936) | "
"Debiasing 46.6% gap reduction (p < 1e-55) | "
"PWAT items: 3=Necrotic Type, 4=Necrotic Amount, "
"5=Granulation Type, 6=Granulation Amount, "
"7=Edges, 8=Periulcer Skin")
draw.text((24, y - 1), txt, fill=COL_INK_MUTE, font=_font_r(11))
# ββ Public API βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def render_integrated_report(
original_rgb: np.ndarray,
binary_overlay_rgb: np.ndarray,
multiclass_overlay_rgb: np.ndarray,
result,
) -> np.ndarray:
"""Render the integrated dashboard as a single image.
Args:
original_rgb: (H, W, 3) RGB uint8 β uploaded image
binary_overlay_rgb: (H, W, 3) RGB uint8 β binary mask overlay
multiclass_overlay_rgb: (H, W, 3) RGB uint8 β multiclass overlay
result: AnalysisResult with class_distribution, fitzpatrick, pwat
Returns:
np.ndarray RGB uint8 of shape (1200, 1920, 3)
"""
canvas = Image.new("RGB", (DASH_W, DASH_H), COL_BG)
draw = ImageDraw.Draw(canvas, "RGBA")
_draw_header(canvas, draw)
_draw_image_strip(canvas, draw,
original_rgb, binary_overlay_rgb, multiclass_overlay_rgb,
result.class_distribution)
pad = 20
row_y0 = 490
row_y1 = DASH_H - 56
fitz_w = 720
fitz_x1 = pad
fitz_x2 = fitz_x1 + fitz_w
pwat_x1 = fitz_x2 + pad
pwat_x2 = DASH_W - pad
_draw_fitzpatrick_card(draw, result.fitzpatrick,
fitz_x1, row_y0, fitz_x2, row_y1)
_draw_pwat_card(draw, result.pwat,
pwat_x1, row_y0, pwat_x2, row_y1)
_draw_footer(draw)
return np.array(canvas)
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