Cant you probably just look up the JS code of the router page and see what requests it sends?
i am stuck when i have ti submet where thay aked if im a android
# compare_icon_fmt.py
import cv2
import numpy as np
from dataclasses import dataclass
from typing import Tuple, List
# ===================== T H A M S Ố & C ᾳ U H Ì N H =====================
@dataclass
class RedMaskParams:
# Dải đỏ HSV đôi: [0..10] U [170..180]
lower1: Tuple[int, int, int] = (0, 80, 50)
upper1: Tuple[int, int, int] = (10, 255, 255)
lower2: Tuple[int, int, int] = (170, 80, 50)
upper2: Tuple[int, int, int] = (180, 255, 255)
open_ksize: int = 3
close_ksize: int = 5
@dataclass
class CCParams:
dilate_ksize: int = 3
min_area: int = 150
max_area: int = 200000
aspect_min: float = 0.5
aspect_max: float = 2.5
pad: int = 2
@dataclass
class FMTParams:
hann: bool = True
eps: float = 1e-3
min_scale: float = 0.5
max_scale: float = 2.0
@dataclass
class MatchParams:
ncc_threshold: float = 0.45
canny_low: int = 60
canny_high: int = 120
# ===================== 1) LOAD & BINARIZE =====================
def load_and_binarize(path: str):
img_bgr = cv2.imread(path, cv2.IMREAD_COLOR)
if img_bgr is None:
raise FileNotFoundError(f"Không thể đọc ảnh: {path}")
rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
gray = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2GRAY)
_, binarized = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
return img_bgr, rgb, binarized
# ===================== 2) TEMPLATE BIN + INVERT =====================
def binarize_and_invert_template(tpl_bgr):
tpl_gray = cv2.cvtColor(tpl_bgr, cv2.COLOR_BGR2GRAY)
_, tpl_bin = cv2.threshold(tpl_gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
tpl_inv = cv2.bitwise_not(tpl_bin)
return tpl_bin, tpl_inv
# ===================== 3) RED MASK =====================
def red_mask_on_dashboard(dash_bgr, red_params: RedMaskParams):
hsv = cv2.cvtColor(dash_bgr, cv2.COLOR_BGR2HSV)
m1 = cv2.inRange(hsv, red_params.lower1, red_params.upper1)
m2 = cv2.inRange(hsv, red_params.lower2, red_params.upper2)
mask = cv2.bitwise_or(m1, m2)
if red_params.open_ksize > 0:
k = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (red_params.open_ksize,)*2)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, k)
if red_params.close_ksize > 0:
k = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (red_params.close_ksize,)*2)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, k)
return mask
def apply_mask_to_binarized(binarized, mask):
return cv2.bitwise_and(binarized, binarized, mask=mask)
# ===================== 4) DILATE + CONNECTED COMPONENTS =====================
def find_candidate_boxes(masked_bin, cc_params: CCParams) -> List[Tuple[int,int,int,int]]:
k = cv2.getStructuringElement(cv2.MORPH_RECT, (cc_params.dilate_ksize,)*2)
dil = cv2.dilate(masked_bin, k, iterations=1)
num_labels, labels, stats, _ = cv2.connectedComponentsWithStats((dil>0).astype(np.uint8), connectivity=8)
boxes = []
H, W = masked_bin.shape[:2]
for i in range(1, num_labels):
x, y, w, h, area = stats[i]
if area < cc_params.min_area or area > cc_params.max_area:
continue
aspect = w / (h + 1e-6)
if not (cc_params.aspect_min <= aspect <= cc_params.aspect_max):
continue
x0 = max(0, x - cc_params.pad)
y0 = max(0, y - cc_params.pad)
x1 = min(W, x + w + cc_params.pad)
y1 = min(H, y + h + cc_params.pad)
boxes.append((x0, y0, x1-x0, y1-y0))
return boxes
# ===================== 5) CROP CHẶT TEMPLATE =====================
def tight_crop_template(tpl_inv):
cnts, _ = cv2.findContours(tpl_inv, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if not cnts:
return tpl_inv
x, y, w, h = cv2.boundingRect(max(cnts, key=cv2.contourArea))
return tpl_inv[y:y+h, x:x+w]
# ===================== 6) FOURIER–MELLIN (scale, rotation) =====================
def _fft_magnitude(img: np.ndarray, use_hann=True, eps=1e-3) -> np.ndarray:
if use_hann:
hann_y = cv2.createHanningWindow((img.shape[1], 1), cv2.CV_32F)
hann_x = cv2.createHanningWindow((1, img.shape[0]), cv2.CV_32F)
window = hann_x @ hann_y
img = img * window
dft = cv2.dft(img, flags=cv2.DFT_COMPLEX_OUTPUT)
dft_shift = np.fft.fftshift(dft, axes=(0,1))
mag = cv2.magnitude(dft_shift[:,:,0], dft_shift[:,:,1])
mag = np.log(mag + eps)
mag = cv2.normalize(mag, None, 0, 1, cv2.NORM_MINMAX)
return mag
def _log_polar(mag: np.ndarray) -> Tuple[np.ndarray, float]:
center = (mag.shape[1]//2, mag.shape[0]//2)
max_radius = min(center[0], center[1])
M = mag.shape[1] / np.log(max_radius + 1e-6)
lp = cv2.logPolar(mag, center, M, cv2.WARP_FILL_OUTLIERS + cv2.INTER_LINEAR)
return lp, M
def fourier_mellin_register(img_ref: np.ndarray, img_mov: np.ndarray, fmt_params: FMTParams):
a = cv2.normalize(img_ref.astype(np.float32), None, 0, 1, cv2.NORM_MINMAX)
b = cv2.normalize(img_mov.astype(np.float32), None, 0, 1, cv2.NORM_MINMAX)
amag = _fft_magnitude(a, use_hann=fmt_params.hann, eps=fmt_params.eps)
bmag = _fft_magnitude(b, use_hann=fmt_params.hann, eps=fmt_params.eps)
alp, M = _log_polar(amag)
blp, _ = _log_polar(bmag)
shift, response = cv2.phaseCorrelate(alp, blp)
# phaseCorrelate trả (shiftX, shiftY)
shiftX, shiftY = shift
cols = alp.shape[1]
scale = np.exp(shiftY / (M + 1e-9))
rotation = -360.0 * (shiftX / (cols + 1e-9))
scale = float(np.clip(scale, fmt_params.min_scale, fmt_params.max_scale))
rotation = float(((rotation + 180) % 360) - 180)
return scale, rotation, float(response)
def warp_template_by(scale: float, rotation_deg: float, tpl_gray: np.ndarray, target_size: Tuple[int, int]):
h, w = tpl_gray.shape[:2]
center = (w/2, h/2)
M = cv2.getRotationMatrix2D(center, rotation_deg, scale)
warped = cv2.warpAffine(tpl_gray, M, (w, h), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=0)
warped = cv2.resize(warped, (target_size[0], target_size[1]), interpolation=cv2.INTER_LINEAR)
return warped
# ===================== 7) MATCH SCORE (robust) =====================
def edge_preprocess(img_gray: np.ndarray, mp: MatchParams):
# CLAHE để chống ảnh phẳng
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
g = clahe.apply(img_gray)
edges = cv2.Canny(g, mp.canny_low, mp.canny_high)
# Nếu cạnh quá ít → dùng gradient magnitude
if np.count_nonzero(edges) < 0.001 * edges.size:
gx = cv2.Sobel(g, cv2.CV_32F, 1, 0, ksize=3)
gy = cv2.Sobel(g, cv2.CV_32F, 0, 1, ksize=3)
mag = cv2.magnitude(gx, gy)
mag = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
return mag
# Dãn cạnh nhẹ
k = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
edges = cv2.dilate(edges, k, iterations=1)
return edges
def _nan_to_val(x: float, val: float = -1.0) -> float:
return float(val) if (x is None or (isinstance(x, float) and (x != x))) else float(x)
def ncc_score(scene: np.ndarray, templ: np.ndarray) -> float:
Hs, Ws = scene.shape[:2]
Ht, Wt = templ.shape[:2]
if Hs < Ht or Ws < Wt:
pad = np.zeros((max(Hs,Ht), max(Ws,Wt)), dtype=scene.dtype)
pad[:Hs,:Ws] = scene
scene = pad
# 1) TM_CCOEFF_NORMED
res = cv2.matchTemplate(scene, templ, cv2.TM_CCOEFF_NORMED)
s1 = _nan_to_val(res.max())
# 2) Fallback: TM_CCORR_NORMED
s2 = -1.0
if s1 <= -0.5:
res2 = cv2.matchTemplate(scene, templ, cv2.TM_CCORR_NORMED)
s2 = _nan_to_val(res2.max())
# 3) Fallback cuối: IoU giữa 2 mask nhị phân
if s1 <= -0.5 and s2 <= 0:
t = templ
sc = scene
if sc.shape != t.shape:
sc = cv2.resize(sc, (t.shape[1], t.shape[0]), interpolation=cv2.INTER_NEAREST)
_, tb = cv2.threshold(t, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
_, sb = cv2.threshold(sc, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
inter = np.count_nonzero(cv2.bitwise_and(tb, sb))
union = np.count_nonzero(cv2.bitwise_or(tb, sb))
iou = inter / union if union > 0 else 0.0
return float(iou)
return max(s1, s2)
def thicken_binary(img: np.ndarray, ksize: int = 3, iters: int = 1) -> np.ndarray:
k = cv2.getStructuringElement(cv2.MORPH_RECT, (ksize,ksize))
return cv2.dilate(img, k, iterations=iters)
# ===================== P I P E L I N E C H Í N H =====================
def find_icon_with_fmt(
dashboard_path: str,
template_path: str,
red_params=RedMaskParams(),
cc_params=CCParams(),
fmt_params=FMTParams(),
match_params=MatchParams(),
):
# 1) Dashboard: RGB + bin
dash_bgr, dash_rgb, dash_bin = load_and_binarize(dashboard_path)
# 2) Template: bin + invert
tpl_bgr = cv2.imread(template_path, cv2.IMREAD_COLOR)
if tpl_bgr is None:
raise FileNotFoundError(f"Không thể đọc template: {template_path}")
tpl_bin, tpl_inv = binarize_and_invert_template(tpl_bgr)
# 3) Lọc đỏ & áp mask lên ảnh nhị phân dashboard
redmask = red_mask_on_dashboard(dash_bgr, red_params)
dash_masked = apply_mask_to_binarized(dash_bin, redmask)
# 4) Dãn + tìm CC để lấy candidate boxes
boxes = find_candidate_boxes(dash_masked, cc_params)
# 5) Cắt chặt template & chuẩn bị phiên bản grayscale
tpl_tight = tight_crop_template(tpl_inv)
tpl_tight_gray = cv2.GaussianBlur(tpl_tight, (3,3), 0)
# Tiền xử lý cạnh cho template
tpl_edges = edge_preprocess(tpl_tight_gray, match_params)
best = {
"score": -1.0,
"box": None,
"scale": None,
"rotation": None
}
dash_gray = cv2.cvtColor(dash_bgr, cv2.COLOR_BGR2GRAY)
for (x, y, w, h) in boxes:
roi = dash_gray[y:y+h, x:x+w]
if roi.size == 0 or w < 8 or h < 8:
continue
# Resize tạm cho FMT
tpl_norm = cv2.resize(tpl_tight_gray, (w, h), interpolation=cv2.INTER_LINEAR)
roi_norm = cv2.resize(roi, (w, h), interpolation=cv2.INTER_LINEAR)
# 6) FMT ước lượng scale/rotation (có fallback)
try:
scale, rotation, resp = fourier_mellin_register(tpl_norm, roi_norm, fmt_params)
except Exception:
scale, rotation, resp = 1.0, 0.0, 0.0
warped = warp_template_by(scale, rotation, tpl_tight_gray, target_size=(w, h))
# (tuỳ chọn) làm dày biên template
warped = thicken_binary(warped, ksize=3, iters=1)
# 7) Tính điểm khớp trên đặc trưng robust
roi_feat = edge_preprocess(roi, match_params)
warped_feat = edge_preprocess(warped, match_params)
score = ncc_score(roi_feat, warped_feat)
if score > best["score"]:
best.update({
"score": score,
"box": (x, y, w, h),
"scale": scale,
"rotation": rotation
})
return {
"best_score": best["score"],
"best_box": best["box"], # (x, y, w, h) trên dashboard
"best_scale": best["scale"],
"best_rotation_deg": best["rotation"],
"pass": (best["score"] is not None and best["score"] >= match_params.ncc_threshold),
"num_candidates": len(boxes),
}
# ===================== V Í D Ụ C H Ạ Y =====================
if __name__ == "__main__":
# ĐỔI 2 ĐƯỜNG DẪN NÀY THEO MÁY BẠN
DASHBOARD = r"\Icon\dashboard.jpg"
TEMPLATE = r"\Icon\ID01.jpg"
result = find_icon_with_fmt(
dashboard_path=DASHBOARD,
template_path=TEMPLATE,
red_params=RedMaskParams(), # nới dải đỏ nếu cần
cc_params=CCParams(min_area=60, max_area=120000, pad=3),
fmt_params=FMTParams(min_scale=0.6, max_scale=1.8),
match_params=MatchParams(ncc_threshold=0.55, canny_low=50, canny_high=130)
)
print("=== KẾT QUẢ ===")
for k, v in result.items():
print(f"{k}: {v}")
# Vẽ khung best match để kiểm tra nhanh
if result["best_box"] is not None:
img = cv2.imread(DASHBOARD)
x, y, w, h = result["best_box"]
cv2.rectangle(img, (x,y), (x+w, y+h), (0,255,0), 2)
cv2.putText(img, f"NCC={result['best_score']:.2f}", (x, max(0,y-8)),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0), 2, cv2.LINE_AA)
cv2.imshow("Best match", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
Hi i am using but it don't find correct image. Please help me check
code not run
import { Directive, ElementRef, HostListener } from '@angular/core';
@Directive({
selector: '[formatDate]', // Este é o seletor que você usará no HTML
standalone: true // Torna a diretiva autônoma (não precisa ser declarada em um módulo)
})
export class FormataDateDirective {
constructor(private el: ElementRef) {}
/**
* O HostListener escuta eventos no elemento hospedeiro (o <input>).
* Usamos o evento 'input' porque ele captura cada alteração,
* incluindo digitação, colagem e exclusão de texto.
* @param event O evento de entrada disparado.
*/
@HostListener('input', ['$event'])
onInputChange(event: Event): void {
const inputElement = event.target as HTMLInputElement;
let inputValue = inputElement.value.replace(/\D/g, ''); // Remove tudo que não for dígito
// Limita a entrada a 8 caracteres (DDMMAAAA)
if (inputValue.length > 8) {
inputValue = inputValue.slice(0, 8);
}
let formattedValue = '';
// Aplica a formatação DD/MM/AAAA conforme o usuário digita
if (inputValue.length > 0) {
formattedValue = inputValue.slice(0, 2);
}
if (inputValue.length > 2) {
formattedValue = `${inputValue.slice(0, 2)}/${inputValue.slice(2, 4)}`;
}
if (inputValue.length > 4) {
formattedValue = `${inputValue.slice(0, 2)}/${inputValue.slice(2, 4)}/${inputValue.slice(4, 8)}`;
}
// Atualiza o valor do campo de entrada
inputElement.value = formattedValue;
}
/**
* Este listener lida com o pressionamento da tecla Backspace.
* Ele garante que a barra (/) seja removida junto com o número anterior,
* proporcionando uma experiência de usuário mais fluida.
*/
@HostListener('keydown.backspace', ['$event'])
onBackspace(event: KeyboardEvent): void {
const inputElement = event.target as HTMLInputElement;
const currentValue = inputElement.value;
if (currentValue.endsWith('/') && currentValue.length > 0) {
// Remove a barra e o número anterior de uma vez
inputElement.value = currentValue.slice(0, currentValue.length - 2);
// Previne o comportamento padrão do backspace para não apagar duas vezes
event.preventDefault();
}
}
}
<main class="center"> <router-outlet></router-outlet> <input type="text" placeholder="DD/MM/AAAA" [formControl]="dateControl" formatDate maxlength="10"
</main>
Seems that it is a common issue, so please vote at https://github.com/angular/angular/issues/64553
this was so helpful, I finally got my toaster to cook a pizza in the morning
And how would I go about this when I want this to work with CUDA.jl CuArrays as well?
Ever solved this?
Tried everything I could find on this topic. Works on all my devices except Android.
Eventually tried 192,0,2,1 instead and this works on my Android just fine.
Encountered same issue where the latest chromium doesn't work on Vercel. Has anyone fix this similar problem? Would've been so helpful.
SonarQube now officially supports Rust:
https://www.sonarsource.com/blog/introducing-rust-in-sonarqube/
i have some issue to validate
C:\Users\grigore.ionescu\WORK\ITC\2025-05-SAFT-Stock-Baan-5\duk_SAFT_2025_10\dist>java -jar DUKIntegrator_AnLunaUI.jar -v D406T C:\Users\grigore.ionescu\WORK\ITC\2025-05-SAFT-Stock-Baan-5\D406\D406\DECLR_2009_1_D406T_I0_20250807.xml $ $ an=2025 luna=10
an:2025
luna:10
an:2025
luna:10
mode=1
XXXXX C:\Users\grigore.ionescu\WORK\ITC\2025-05-SAFT-Stock-Baan-5\duk_SAFT_2025_10\dist\saft_counter.csv
in parseXml
inainte an si luna:2025...10
an:2025 luna:10
VALIDATION FOR TYPE [T]
EXPECTED SECTIONS: [Sections{name=Account, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:71, right:-1, firstCh:73, id:16450,id=72, absPath=AuditFile/MasterFiles/GeneralLedgerAccounts/Account}]}, Sections{name=Customer, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:94, right:-1, firstCh:96, id:16470,id=95, absPath=AuditFile/MasterFiles/Customers/Customer}]}, Sections{name=Supplier, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:145, right:-1, firstCh:147, id:16475,id=146, absPath=AuditFile/MasterFiles/Suppliers/Supplier}]}, Sections{name=TaxTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:196, right:-1, firstCh:198, id:94,id=197, absPath=AuditFile/MasterFiles/TaxTable/TaxTableEntry}]}, Sections{name=UOMTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:215, right:-1, firstCh:217, id:108,id=216, absPath=AuditFile/MasterFiles/UOMTable/UOMTableEntry}]}, Sections{name=AnalysisTypeTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:219, right:-1, firstCh:221, id:111,id=220, absPath=AuditFile/MasterFiles/AnalysisTypeTable/AnalysisTypeTableEntry}]}, Sections{name=Product, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:229, right:-1, firstCh:231, id:120,id=230, absPath=AuditFile/MasterFiles/Products/Product}]}, Sections{name=GeneralLedgerEntries, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:354, right:356, firstCh:-1, id:184,id=355, absPath=AuditFile/GeneralLedgerEntries/NumberOfEntries}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:354, right:357, firstCh:-1, id:185,id=356, absPath=AuditFile/GeneralLedgerEntries/TotalDebit}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:354, right:358, firstCh:-1, id:186,id=357, absPath=AuditFile/GeneralLedgerEntries/TotalCredit}, SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:354, right:-1, firstCh:359, id:187,id=358, absPath=AuditFile/GeneralLedgerEntries/Journal}]}, Sections{name=SalesInvoices, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:417, right:419, firstCh:-1, id:184,id=418, absPath=AuditFile/SourceDocuments/SalesInvoices/NumberOfEntries}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:417, right:420, firstCh:-1, id:185,id=419, absPath=AuditFile/SourceDocuments/SalesInvoices/TotalDebit}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:417, right:421, firstCh:-1, id:186,id=420, absPath=AuditFile/SourceDocuments/SalesInvoices/TotalCredit}, SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:417, right:-1, firstCh:422, id:16601,id=421, absPath=AuditFile/SourceDocuments/SalesInvoices/Invoice}]}, Sections{name=PurchaseInvoices, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:614, right:616, firstCh:-1, id:184,id=615, absPath=AuditFile/SourceDocuments/PurchaseInvoices/NumberOfEntries}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:614, right:617, firstCh:-1, id:185,id=616, absPath=AuditFile/SourceDocuments/PurchaseInvoices/TotalDebit}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:614, right:618, firstCh:-1, id:186,id=617, absPath=AuditFile/SourceDocuments/PurchaseInvoices/TotalCredit}, SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:614, right:-1, firstCh:619, id:16601,id=618, absPath=AuditFile/SourceDocuments/PurchaseInvoices/Invoice}]}, Sections{name=Payments, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:811, right:813, firstCh:-1, id:184,id=812, absPath=AuditFile/SourceDocuments/Payments/NumberOfEntries}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:811, right:814, firstCh:-1, id:185,id=813, absPath=AuditFile/SourceDocuments/Payments/TotalDebit}, SECTION_ELEMENTS{nodeStruct=min:0, max:1, cnt:0, parent:811, right:815, firstCh:-1, id:186,id=814, absPath=AuditFile/SourceDocuments/Payments/TotalCredit}, SECTION_ELEMENTS{nodeStruct=min:0, max:2147483647, cnt:0, parent:811, right:-1, firstCh:816, id:265,id=815, absPath=AuditFile/SourceDocuments/Payments/Payment}]}]
SECTION DETECTED: Sections{name=TaxTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:1, max:2147483647, cnt:1, parent:196, right:-1, firstCh:198, id:94,id=197, absPath=AuditFile/MasterFiles/TaxTable/TaxTableEntry}]}
SECTION DETECTED: Sections{name=UOMTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:1, max:2147483647, cnt:1, parent:215, right:-1, firstCh:217, id:108,id=216, absPath=AuditFile/MasterFiles/UOMTable/UOMTableEntry}]}
SECTION DETECTED: Sections{name=MovementTypeTableEntry, elements=[SECTION_ELEMENTS{nodeStruct=min:0, max:0, cnt:1, parent:225, right:-1, firstCh:227, id:117,id=226, absPath=AuditFile/MasterFiles/MovementTypeTable/MovementTypeTableEntry}]}
1.
Erori la validare fisier: C:\Users\grigore.ionescu\WORK\ITC\2025-05-SAFT-Stock-Baan-5\D406\D406\DECLR_2009_1_D406T_I0_20250807.xml
Erorile au fost scrise in fisierul: C:\Users\grigore.ionescu\WORK\ITC\2025-05-SAFT-Stock-Baan-5\D406\D406\DECLR_2009_1_D406T_I0_20250807.xml.err.txt
and the error file contains:
F: MasterFiles (1) sectiune MovementTypeTable (1) sectiune MovementTypeTableEntry (1) sectiune Description (1)
eroare structura: elementul 'MovementType' a depasit numarul maxim de aparitii (0); a aparut de 1 ori
That somehow implies that the DUKE validatpr does not take in consideration is to validate a D406T declaration for move of goods and stock.
Can anyone help with some insights ?
The --repl option is no longer supported. See https://issues.chromium.org/issues/40257772#comment2
I found interesting answer. May be helpful: https://nmmhelp.getnerdio.com/hc/en-us/community/posts/35207061281549-In-Place-Upgrade-Win11-to-24h2
I am also having the same issue, inside the github the graph is visible however after pushing the code into the github, the github is unbale to render this graphs . Don't no what exactly issue is ?
I'm using springboot 3.4.1
I want to capture http request body and http response body but opentelemetry does not offer this out of the box.
does creating an extension is the best way to do this?
anyone has created this before ?
My issue was that in the raw query I was using the @parameters (that were strings) surrounded with single quotes. Removing the single quotes solved my problem.
05.11.1993
> ----------
05.11.1993Yes, this can likely be done with a Docusign CLM Document Smart Rule, but it requires a more advanced configuration using XPath within the Rename action to dynamically capture the parent folder name and retain the original document name.
Your previous attempt failed because the "Rename" action, when used with a literal value, completely replaces the document name instead of appending or prepending to it.
You can refer to this link for an example: https://community.docusign.com/clm-112/rename-documents-using-attributes-2845
Thanks and regards,
Mahmoud
I noticed when I started debugging, at 53 seconds the error was like this
I hope you’re doing well. I just wanted to check if you were able to find any solution yet?
I just used PG Admin to create snapshot and restore it in new database in new AWS Lightsail account.enter image description here
May God keep you in good health my friend! Thank you!
Editing x32, x64, etc. in the end of the URLs gives better quality icons if needed
https://ssl.gstatic.com/docs/doclist/images/mediatype/icon_1_spreadsheet_x32.png
https://ssl.gstatic.com/docs/doclist/images/mediatype/icon_1_spreadsheet_x64.png
I think it's the file name. try removing the space before the dot.
Kindly take a look at my recent blog to learn how this can be achieved.
https://pothiarunmca.blogspot.com/2025/10/reusable-javascript-function-to.html
hmm, nice. Its working or not? I am curious about it.
From the introduction and illustration you seem to be describing representing data in triplets. This is common in graph databases (specifically property graphs). Have you considered a property graph, and the openCypher query language which is tailored to it?
Ok, thank you President Jam for your help
http://192.168.0.1.comSM-A556E - samsung/a55xnsxx/a55x:16/BP2A.250605.031.A3/A556EXXUACYIA:user/release-keys
Cool post, great instructions, thanks.
Does anyone know if this can be done with WSA (Subsystem for Android) too?
Me encontré con el mismo problema y logré resolverlo utilizando Java 21 junto con JJWT 0.12.5 y 0.13.0.
La solución fue actualizar el método de parsing del token de la siguiente forma:
/**
* Devuelve todos los claims (payload) del token JWT.
*/
public Claims parseClaims(String token) {
return Jwts.parser()
.verifyWith(secretKey)
.build()
.parseSignedClaims(token)
.getPayload();
}
I created a separate bundle for it: https://github.com/savinmikhail/symfony-profiler-response-bundle, see also https://github.com/symfony/symfony/issues/21168
For people who have the same problem while editing an css file in vs. I have used the answer in this link and that worked for me.
Hi, please tell me, I have an INVALID AUTH KEY. What can I do? I replenished my wallet, now I can't withdraw money
did you find the omnik register list.
regards
marc
https://www.youtube.com/watch?v=FxeeCxQGW9U&feature=youtu.be.
https://www.youtube.com/watch?v=FxeeCxQGW9U.
Can someone please tell me what name this YouTube channel is?
I have the Same Problem.
I solve it by using an observable.
toObservable(mySignalFromStore).subscribe(...)
I dont know If this is THE solution.
When using the tiffsep1 driver, how can I set the independent color separation plate angles C=15, M=75, Y=0, K=45? I have tried many methods but none of them worked. The converted color separation plate images all have dots at the same Angle
Found the Fix to it. Go to Disk Utility when screen loads up and format the disk with supported Apple File Format System!
Refer here: https://support.apple.com/guide/disk-utility/file-system-formats-dsku19ed921c/22.7/mac/26
i having the same problem if you find the solution can you help me out with it
You can find the solution for device targeting API level >=36 in here - https://github.com/flutter/flutter/issues/168635#issuecomment-3417866156
adsadsdasasd
DAS
DA
AD
S
DSA
SD
just use winboat, its a windows in a linux
I recently wrote a C-to-Brainfuck compiler. Here's my write-up on how it works.
Top Thanks for the code it finally works fine :)
Look at the migration guide info: https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/client-configuration.html#client-configuration-http
I hope you’re doing well. I’m currently encountering the same issue with Angular 17 and AngularFire when running unit tests using Jasmine + Karma. The error message says: “AngularFireModule is not provided in AppModule”, even though I’m properly configuring the Firebase providers inside the test setup.
I was wondering if you eventually found a reliable solution or workaround for this? Any insights or updated configuration examples for Angular 17 would be greatly appreciated. Thanks in advance for your help!
My tag is Gael_et_co sry about that ^^
It looks like url rewrite has been added:
https://aws.amazon.com/blogs/networking-and-content-delivery/introducing-url-and-host-header-rewrite-with-aws-application-load-balancers/
but I can't get it to work :(
Yyghnzbsbsbshdhd
Jsjsjshshshshshshshshshshhshshs
what is this for I wanna learned
I see that this is an older problem, but to log in to the vault through C# do I need to have an API license or is it enough to have a classic M-files license? And what is the exact address for logging in to the vault please? I am stuck on this problem.
Can we embede public facebook profile into iframe ?
The client credentials flow iss : "https://sts.windows.net/ instead "https://login.microsoftonline.com which is the case for login flow even though i set API version 2 , in client credentials it always get version 1 i am missing something in configuration ?
I had this same issue with my installation -- did you grab the code signing cert? That fixed it for me, and it doesn't automatically download to the certs folder in the layout.
Which certificate broker did you use? I have the same issue with a Sectigo certificate and might try LetsEncrypt to see if the certificate itself is related in one way or another.
Have you solved it? I am also looking for a solution.
I encountered the same problem.
I hope you are doing well. My name is Amina, and I am reaching out to discuss the possibility of publishing a guest post on your website. I would be grateful if you could kindly provide details regarding your guest posting requirements.
Specifically, I would like to know about the following:
Guest Post Policy
Do you accept guest posts on your website?
What are your content quality and niche requirements?
Links & SEO
Do you allow dofollow or nofollow backlinks?
How many backlinks are allowed in a single guest post?
Do you allow link insertion in existing articles?
Publishing & Duration
How many days does it usually take to review and publish a guest post?
For how long will the post remain live?
3 months
6 months
1 year
Lifetime
Other Details
Do you charge any publishing fees or is it free?
Any formatting or style guidelines that I should follow?
I am happy to provide unique, high-quality, and well-researched content that aligns with your website’s audience and standards.
Looking forward to your response.
Best Regards,
Amina
I have tried all the solutions mentioned above, but I am still getting the error below in the SMTP server logs. Any suggestion would be appreciated.
Java 1.8
SMTP Port: 25 (as provided by our SMTP team)
Javax.mail: 1.6.2
TLS negotiation failed with error SocketError
Remote(SocketError)
If I have one templete and 1 icon but Icon is similar, not cut from templete. Do we find it in templete?
fig.savefig('test.png', bbox_inches='tight') works.
Yeah, Have the same issue. After I scan NFC tag, the phone vibrates, OnNewIntent function starts and passes by this condition(so it is false). I really hope someone to answer
Bro, same issue, did u solve it?
None of this worked in case of Large and Medium Top App Bar.
Do you have any other solution?
Model Derivative POST {urn}/references doesn't support RVT files as per @eason-kang comment. The ZIP file is the only option.
To have access on the account_usage viewes, you need IMPORTED PRIVILEGEDES ON DATABASE SNOWFLAKE .
You need to add this in the manifest.yml file. Refer to this link to check the more:
This error is not related to CKEditor but broken File link with an umlaut. By removing the umlaut this can fix this issue.
Please refer this tutorial. Believe it helps.
https://docs.typo3.org/m/typo3/reference-exceptions/main/en-us/Exceptions/1320286857.html
There is much easier way, check this post: https://medium.com/@danielcrompton5/liquid-glass-text-effect-in-swiftui-for-macos-ios-7468ced04e35
Use this; Life will become Easy :)
https://tools.simonwillison.net/incomplete-json-printer
check this video https://youtu.be/-WteiPaUv-U it has clear explanation.
In order to fix the issue, I had to Re-Register the application in ADB2C tenant specifically with below Account Type under Authentication -
The only solution I've found is to install this extension: https://marketplace.visualstudio.com/items?itemName=FortuneWang.search-folder
Refer to this article Sucuri bypass techniques
How did you manage to solve it, I'm facing the same error now!
Github released rulesets which now allow, for given branches, specific allowed merge methods
I had this issue with a payroll system displaying REP-0606 error. After resizing the image to below 8KB it finally worked. Thanks for the insights!
From Spring 4.3 version, dependency will be considered automatically without adding @Autowired. But @Autowired is mandatory if multiple constructors are used.
after uninstalling some latests updates iis working again
I'm having the same problem with my clients, and I have to uninstall the security update KB5066835 I'm having the same problem with my clients, and I have to uninstall the security update KB5066835 to make it work.
If someone has a better solution, it would be better.
My app is experiencing the same issue — the watchdog stack trace is almost identical to the one you provided. Are you able to reproduce this situation consistently?
They sold his shit or stole it from him he sees someone else which is my mom slim draught i telling you they stole his laptop I've been rape by dog at the trailer park skyway and they killed tammy in front of me I've been raped none stop and pregnant in library in Renton they killed her at the trailer park cut her up in front me. Raily is asshole to me rude has fuck. I'm done I can't get my EBT or SSI back. I CANT MAKE EEMAIL SOMEONE HACKS IN MY STUFF. CHECK ELLENBRUG FOOR TAMMY THAT WHERE SHE WAS LIVING AND CHECK 2223 177TH ST SE BOTHELL WA 98012 CHECK LORN TOO HIS GRANDPA INVOVLE MILISING ME WIHT A DOG AND SHOT GUN. I NEED KNOW HHOW MANY MISSING IN COURT EVERY COUNTY AND MISSING ON EVERY STREET REPORT MISSING SO I KNOW BECASUE THERE ARE FEW PLACES KILLING SWAT TEAM. i WANT THEM DEAD OR CUFF AND I WANT MY KLOAD THEY STOLE FROM ME THE FAKE DJ MOM IS UP THERE TOO EVERYONE YOU WANT IS THERE
did you find any solution for this?
As far as I know we have to build the entire thing on our own using the data we get form webhook
@Teshan N. how did you fix this error?, I also have the same error
nice script. Do get an error message, because my adapter has spaces in the name. how can I fix this?
Did you manage to fix it ? I've just finished updating my react native due to some new playstore compliance issues and was testing the pipes and release the ios geolocation isn't working on the release build but works fine locally on debug. Maybe it could be the same issue or something similar
Did you ever get this to work and if so, how?
Check your zod version -- I was hitting the same error, but resolved it after downgrading to zod@3. https://www.npmjs.com/package/@openai/agents#installation
I have a similar problem with https://banno.com/a/oidc-provider/api/v0/auth, which is returning the response below. My client id is 05815133-6c9e-4fa0-9e53-d56b753d1800. I'm using the Node sample application for this test.
{"error":"invalid_client","error_description":"client is invalid","state":"f2pg3di9cdh9h3luvopcf","iss":"https://banno.com/a/oidc-provider/api/v0","request_id":"8f4b1950351fc5eca23a55d5b0548314"}
idk man, try asking chatgpt or copilot tbh, coding kinda hard
I am doing the exact same thing on a WatchOS application. Same results, works in simulator but not on watch. I get the same error message.
Hoping this reply might get this topic going again
I want to ask similar questions. What should I write in the scale fill manual function when I have more than one information in the legend?
Can you tell me please, what is the critererea of stopping? i look that you don't have evaluation dataset !!
how do I get the user's role form the JWT, can I extend it wihtout callbacks? I know about using the token and session callbacks for it, but thats flimsy, it sometimes fails. any notes?
This blog post https://babichmorrowc.github.io/post/2019-03-18-alpha-hull/ explains how to do it with this package https://github.com/babichmorrowc/hull2spatial?tab=readme-ov-file. It currently outputs Spatial* class objects, but these can be easily converted to terra 'SpatVector' or to 'sf'.
Did you ever get an answer to this?
Hi how or where is the title for a screenshot I had taken and downloaded with lighthouse I need for an evidence to send but I dnt seem to be able to find it can anyone help ???
I was able to approve tools by using the Agents interface within VS Code as described on this page: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/vs-code-agents-mcp
Never found a way to approve through the web UI.
I was able to do it by using custom layers on Nivo