hytos / DTI_PID / WebServer / app.py @ a91e2268
이력 | 보기 | 이력해설 | 다운로드 (3.98 KB)
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from flask import Flask, jsonify, request, render_template |
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import cv2 |
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import numpy as np |
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import sys, os |
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import json, base64 |
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# craft
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sys.path.insert(0, os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master') |
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# service streamer
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sys.path.insert(0, os.path.dirname(os.path.realpath(__file__)) + '\\service_streamer_master') |
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# deep ocr
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#sys.path.insert(0, os.path.dirname(os.path.realpath(__file__)) + '\\deep_text_recognition_benchmark_master')
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app = Flask(__name__) |
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try:
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#from model import get_prediction, batch_prediction
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import text_craft |
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from service_streamer import ThreadedStreamer |
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# for error at 3.8
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import ctypes |
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ctypes.cdll.LoadLibrary('caffe2_nvrtc.dll')
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streamer = ThreadedStreamer(text_craft.get_text_box_batch, batch_size=64)
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except ImportError as ex: |
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ex |
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pass
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@app.route('/') |
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def index(): |
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return 'Hello ID2' |
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@app.route('/requset_license_key/') |
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def requset_license_key(): |
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return render_template('license.html') |
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@app.route('/gen_key', methods=['POST']) |
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def gen_key(): |
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import base64 |
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if request.method == 'POST': |
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r = request |
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key = 'Image Drawing to Intelligent Drawing'
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pw = r.form['Authorization']
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clear = r.form['Computer_Name']
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if pw != 'admin': |
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return 'Invalid Authorization' |
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enc = [] |
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for i in range(len(clear)): |
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key_c = key[i % len(key)]
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enc_c = (ord(clear[i]) + ord(key_c)) % 256 |
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enc.append(enc_c) |
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new_key = base64.urlsafe_b64encode(bytes(enc))
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return 'License Key for ' + clear + ' : ' + new_key.decode('utf-8') |
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@app.route('/symbol_box', methods=['POST']) |
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def symbol_box(): |
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if request.method == 'POST': |
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r = request |
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nparr = np.fromstring(r.data, np.uint8) |
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
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boxes = text_craft.get_text_box(img, img_path=None, score_path=None, trained_model=os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_mlt_25k.pth') |
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return jsonify({'symbol_box': boxes}) |
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@app.route('/text_box', methods=['POST']) |
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def text_box(): |
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if request.method == 'POST': |
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r = request |
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nparr = np.fromstring(r.data, np.uint8) |
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
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#img = img.reshape(1, -1)
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boxes = text_craft.get_text_box(img, img_path=None, score_path=None, trained_model=os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_mlt_25k.pth') |
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return jsonify({'text_box': boxes}) |
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@app.route('/stream_text_box', methods=['POST']) |
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def stream_text_box(): |
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if request.method == 'POST': |
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r = request |
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str_imgs = json.loads(r.data) |
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imgs = [] |
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for str_img in str_imgs: |
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str_img = base64.b64decode(str_img) |
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nparr = np.fromstring(str_img, np.uint8) |
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
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imgs.append(img) |
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boxes_list = [] |
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'''
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for img in imgs:
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# faster
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#boxes = streamer.predict([[img, None, None, os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_ic15_20k.pth']])
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# More accurate
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boxes = streamer.predict([[img, None, None, os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_mlt_25k.pth']])
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boxes_list.append(boxes[0])
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'''
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'''
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infos = []
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for img in imgs:
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infos.append([img, None, None, os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_mlt_25k.pth'])
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boxes = streamer.predict(infos)
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boxes_list = boxes
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'''
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infos = [[None, None, os.path.dirname(os.path.realpath(__file__)) + '\\CRAFT_pytorch_master\\weights\\craft_mlt_25k.pth', imgs]] |
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boxes = streamer.predict(infos) |
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boxes_list = boxes[0]
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return jsonify({'text_box_list': boxes_list}) |
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if __name__ == '__main__': |
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app.run(debug=False)
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#app.run(host='0,0,0,0')
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