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