| # from flask import Flask, request, jsonify, render_template, make_response | |
| # from flask_cors import CORS | |
| from fastapi import FastAPI | |
| 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 | |
| app = FastAPI() | |
| # UPLOAD_FOLDER = './uploads' | |
| # app = Flask(__name__, template_folder='/client', static_folder='/client') | |
| # | |
| # app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER | |
| # | |
| # CORS( | |
| # app, | |
| # supports_credentials=True | |
| # ) | |
| def read_root(): | |
| return {"Hello": "World!"} | |
| # @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, host="0.0.0.0", port=8000) | |