CoolFace
Apppublic

project-sign-language/Sign_language

sourceHugging Facemitupdated 2y agoView on Hugging Face
0likes
main.py60 linesDownload Raw Back to src
1import display_gloss as dg2import synonyms_preprocess as sp3from NLP_Spacy_base_translator import NlpSpacyBaseTranslator 4from flask import Flask,  render_template, Response, request5 6# ---- Initialise Flask App7#8app = Flask(__name__)9 10# ---- Initialise data11#12nlp, dict_docs_spacy = sp.load_spacy_values()13dataset, list_2000_tokens = dg.load_data()14 15# ---- Render the homepage template16#17@app.route('/')18def index():19 20    return render_template('index.html')21 22# ---- Translate english input sentence into gloss sentence23#24@app.route('/translate/', methods=['POST'])25def result():26    27    if request.method == 'POST':28        # ---- Get the raw sentence and translate it to gloss29        #30        sentence = request.form['inputSentence']31        eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=sentence)32        generated_gloss = eng_to_asl_translator.translate_to_gloss()33        gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum() ]34        gloss_sentence_before_synonym = " ".join(gloss_list_lower)35 36        # ---- Substitute gloss tokens with synonyms if not in the common token list37        #38        gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, list_2000_tokens) for gloss in gloss_list_lower]39        gloss_sentence_after_synonym  = " ".join(gloss_list)40 41        # ---- Render the result template with both versions of the gloss sentence42        #43        return render_template('translate.html',\44                                sentence=sentence,\45                                gloss_sentence_before_synonym=gloss_sentence_before_synonym,\46                                gloss_sentence_after_synonym=gloss_sentence_after_synonym)47 48# ---- Generate video streaming from gloss_sentence49#50@app.route('/video_feed')51def video_feed():52    53    sentence = request.args.get('gloss_sentence_to_display', '')54    gloss_list = sentence.split()55    return Response(dg.generate_video(gloss_list, dataset, list_2000_tokens), mimetype='multipart/x-mixed-replace; boundary=frame')56 57if __name__ == "__main__":58    app.debug = True59    app.run(host="0.0.0.0", port=5000, debug=True)60