# app.py - VERSÃO FINAL, COMPLETA E CORRIGIDA import os import cv2 import numpy as np import base64 import tempfile import zipfile import uuid from flask import Flask, request, jsonify, render_template, send_from_directory from werkzeug.utils import secure_filename # --- CONFIGURAÇÃO DA APLICAÇÃO --- app = Flask(__name__) UPLOAD_FOLDER = tempfile.gettempdir() app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024 # 16 MB # --- FUNÇÕES DE PROCESSAMENTO DE IMAGEM --- def process_image(image_path, options): """ Função principal que orquestra o pipeline de processamento de imagem. Versão corrigida para imagens com pistas brancas sobre fundo preto. """ img = cv2.imread(image_path) if img is None: raise ValueError("Não foi possível ler a imagem.") # 1. Converter para escala de cinza gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 2. Pré-processamento (opcional, mas útil) if options.get('enhance_contrast'): clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) gray = clahe.apply(gray) if options.get('remove_noise'): gray = cv2.medianBlur(gray, 3) # 3. Binarização da imagem (CORRIGIDO) # Usamos THRESH_BINARY: pixels claros (acima do threshold) ficam brancos. _, binary_img = cv2.threshold( gray, options.get('threshold'), 255, cv2.THRESH_BINARY ) # 4. LIMPEZA AVANÇADA DOS CONTORNOS kernel = np.ones((2, 2), np.uint8) cleaned_img = cv2.morphologyEx(binary_img, cv2.MORPH_OPEN, kernel, iterations=2) cleaned_img = cv2.morphologyEx(cleaned_img, cv2.MORPH_CLOSE, kernel, iterations=2) # 5. Encontrar os contornos na imagem JÁ LIMPA contours, _ = cv2.findContours( cleaned_img, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE ) # 6. Filtrar contornos muito pequenos min_area = options.get('min_area') filtered_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > min_area] if options.get('smooth_curves'): smoothed_contours = [cv2.approxPolyDP(cnt, 0.001 * cv2.arcLength(cnt, True), True) for cnt in filtered_contours] filtered_contours = smoothed_contours # 7. Gerar pré-visualizações (a função agora existe) previews = generate_previews(img, cleaned_img, filtered_contours) return filtered_contours, previews def generate_previews(original_img, binary_img, contours): """ Função que gera imagens em Base64 para mostrar no frontend. """ contour_preview = np.zeros_like(original_img) cv2.drawContours(contour_preview, contours, -1, (102, 126, 234), 2) def to_base64(img_array): _, buffer = cv2.imencode('.png', img_array) return base64.b64encode(buffer).decode('utf-8') return { 'original': to_base64(original_img), 'binary': to_base64(binary_img), # Mostra a imagem binária já limpa 'contours': to_base64(contour_preview) } # --- FUNÇÕES DE GERAÇÃO DE FICHEIROS --- def create_gerber_manually(contours, img_height, dpi, output_path): """ Cria um ficheiro Gerber a partir de contornos, sem bibliotecas externas. """ scale_factor = 25.4 / dpi precision = 10000 gerber_commands = ["%FSLAX44Y44*%", "%MOMM*%", "%LPD*%"] for contour in contours: gerber_commands.append("G36*") first_point = contour[0][0] x_mm = first_point[0] * scale_factor y_mm = (img_height - first_point[1]) * scale_factor gerber_commands.append(f"X{int(x_mm * precision)}Y{int(y_mm * precision)}D02*") for point in contour[1:]: p = point[0] x_mm = p[0] * scale_factor y_mm = (img_height - p[1]) * scale_factor gerber_commands.append(f"X{int(x_mm * precision)}Y{int(y_mm * precision)}D01*") gerber_commands.append(f"X{int(x_mm * precision)}Y{int(y_mm * precision)}D01*") gerber_commands.append("G37*") gerber_commands.append("M02*") with open(output_path, 'w') as f: f.write("\n".join(gerber_commands) + "\n") def create_drill_file(contours, img_height, dpi, output_path): drill_holes = [] for cnt in contours: area = cv2.contourArea(cnt) perimeter = cv2.arcLength(cnt, True) if perimeter == 0: continue circularity = 4 * np.pi * (area / (perimeter * perimeter)) if 0.8 < circularity < 1.2: (x, y), radius = cv2.minEnclosingCircle(cnt) x_inch, y_inch = x / dpi, (img_height - y) / dpi diameter_inch = (radius * 2) / dpi drill_holes.append({'x': x_inch, 'y': y_inch, 'd': diameter_inch}) if not drill_holes: return False with open(output_path, 'w') as f: f.write("M48\nINCH,LZ\nFMAT,2\n") tools = {} for hole in drill_holes: d_str = f"{hole['d']:.4f}" if d_str not in tools: tools[d_str] = [] tools[d_str].append(hole) tool_id = 1 for d_str, _ in tools.items(): f.write(f"T{tool_id}C{d_str}\n"); tool_id += 1 f.write("%\n") tool_id = 1 for _, holes in tools.items(): f.write(f"T{tool_id}\n") for hole in holes: f.write(f"X{hole['x']:.4f}Y{hole['y']:.4f}\n") tool_id += 1 f.write("M30\n") return True def create_svg(contours, width, height, dpi, output_path): width_mm, height_mm = width / dpi * 25.4, height / dpi * 25.4 svg = f'\n' svg += '\n' svg += f'\n' for contour in contours: points = " ".join([f"{p[0][0]},{p[0][1]}" for p in contour]) svg += f' \n' svg += '\n' with open(output_path, "w") as f: f.write(svg) # --- ROTAS DA API FLASK --- @app.route('/') def index(): return render_template('index.html') @app.route('/process', methods=['POST']) def process_route(): if 'image' not in request.files: return jsonify({'success': False, 'error': 'Nenhum ficheiro'}), 400 file = request.files['image'] if file.filename == '': return jsonify({'success': False, 'error': 'Nenhum ficheiro'}), 400 DPI = 600 try: options = {'threshold': int(request.form.get('threshold', 127)), 'min_area': int(request.form.get('minArea', 100)), 'remove_noise': request.form.get('removeNoise') == 'true', 'enhance_contrast': request.form.get('enhanceContrast') == 'true', 'smooth_curves': request.form.get('smoothCurves') == 'true', 'generate_drill': request.form.get('generateDrill') == 'true'} filename = secure_filename(file.filename) temp_path = os.path.join(app.config['UPLOAD_FOLDER'], filename) file.save(temp_path) # Chamada ao processamento contours, previews = process_image(temp_path, options) session_id = str(uuid.uuid4()) filenames = {'gbr': f"{session_id}.gbr", 'svg': f"{session_id}.svg", 'drl': f"{session_id}.drl", 'zip': f"{session_id}.zip"} paths = {k: os.path.join(app.config['UPLOAD_FOLDER'], v) for k, v in filenames.items()} img_h, img_w = cv2.imread(temp_path).shape[:2] create_gerber_manually(contours, img_h, DPI, paths['gbr']) create_svg(contours, img_w, img_h, DPI, paths['svg']) with open(paths['svg'], 'rb') as f: previews['svg'] = base64.b64encode(f.read()).decode('utf-8') drill_gen = create_drill_file(contours, img_h, DPI, paths['drl']) if options['generate_drill'] else False with zipfile.ZipFile(paths['zip'], 'w') as zf: zf.write(paths['gbr'], os.path.basename(paths['gbr'])) zf.write(paths['svg'], os.path.basename(paths['svg'])) if drill_gen: zf.write(paths['drl'], os.path.basename(paths['drl'])) response_data = {'success': True, 'data': {'previews': previews, 'files': {'zip': filenames['zip'], 'gerber': filenames['gbr'], 'svg': filenames['svg'], 'drill': filenames['drl'] if drill_gen else None}}} os.remove(temp_path) return jsonify(response_data) except Exception as e: app.logger.error(f"Erro no processamento: {e}", exc_info=True) return jsonify({'success': False, 'error': str(e)}), 500 @app.route('/download/') def download_file(filename): return send_from_directory(app.config['UPLOAD_FOLDER'], filename, as_attachment=True) if __name__ == '__main__': app.run(debug=True, port=5000)