| from flask import Flask, request, jsonify, render_template, make_response |
| from flask_cors import CORS |
| import numpy as np |
| import cv2 |
|
|
| from src.color_controls import control_kelvin, control_contrast, control_HSV |
| from src.cyano import Cyanotype |
| from src.prediction import predict_img, optimize_img, update_patch |
| from src.utils import cv_to_pil, pil_to_cv |
|
|
| UPLOAD_FOLDER = './uploads' |
| app = Flask(__name__, template_folder='/client', static_folder='/client') |
|
|
| app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER |
|
|
| CORS( |
| app, |
| supports_credentials=True |
| ) |
|
|
|
|
| @app.route('/api/process', methods=['POST']) |
| def process(): |
| imgfile = request.files['img'] |
| img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8) |
| img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) |
|
|
| data = request.form |
| hue = int(data["hue"]) |
| saturation = float(data["saturation"]) |
| lightness = float(data["lightness"]) |
| contrast = int(data["contrast"]) |
| kelvin = int(data["kelvin"]) |
|
|
| img = control_contrast(img, contrast) |
| img = control_HSV(img, hue, saturation, lightness) |
|
|
| img_pil = cv_to_pil(img) |
| img_pil = control_kelvin(img_pil, kelvin) |
| img = pil_to_cv(img_pil) |
|
|
| response = make_response(cv2.imencode('.png', img)[1].tobytes()) |
| response.headers.set('Content-Type', 'image/png') |
|
|
| return response |
|
|
|
|
| @app.route('/api/predict/<process_name>', methods=['POST']) |
| def predict(process_name): |
| if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']: |
| return jsonify({ 'error': 'process name is invalid' }) |
|
|
| imgfile = request.files['img'] |
| img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8) |
| img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) |
|
|
| if 'colorpatch' in request.files: |
| patchfile = request.files['colorpatch'] |
| patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8) |
| colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR) |
| update_patch(process_name, colorpatch) |
|
|
| img = predict_img(process_name, img) |
|
|
| response = make_response(cv2.imencode('.png', img)[1].tobytes()) |
| response.headers.set('Content-Type', 'image/png') |
|
|
| return response |
|
|
|
|
| @app.route('/api/optimize/<process_name>', methods=['POST']) |
| def optimize(process_name): |
| if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']: |
| return jsonify({ 'error': 'process name is invalid' }) |
|
|
| imgfile = request.files['img'] |
| img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8) |
| img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) |
|
|
| if 'colorpatch' in request.files: |
| patchfile = request.files['colorpatch'] |
| patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8) |
| colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR) |
| update_patch(process_name, colorpatch) |
|
|
| (opt_img, preview_img) = optimize_img(process_name, img) |
|
|
| h, w = preview_img.shape[:2] |
| if process_name.endswith('full'): |
| opt_img = np.reshape(opt_img, (h, w, 3)) |
| else: |
| opt_img = np.reshape(opt_img, (h, w, 1)) |
| opt_img = np.array([[[i[0]] * 3 for i in j] for j in opt_img], dtype=np.uint8) |
|
|
| img = cv2.hconcat([opt_img, preview_img]) |
| response = make_response(cv2.imencode('.png', img)[1].tobytes()) |
| response.headers.set('Content-Type', 'image/png') |
|
|
| return response |
|
|
|
|
| if __name__ == "__main__": |
| app.run(debug=True, port=8000) |
|
|
