def predict():
img = request.files['image']
path = "./static/{}".format(img.filename)
img.save(path)
caption = caption_it.caption_this_image(path)
print(caption)
example_sent = caption
stop_words = set(stopwords.words('english'))
word_tokens = word_tokenize(example_sent)
filtered_sentence = [w for w in word_tokens if not w in stop_words]
filtered_sentence = []
for w in word_tokens:
if w not in stop_words:
filtered_sentence.append(w)
print(word_tokens)
print(filtered_sentence)
os.remove(path)
return jsonify(msg=caption, tags=filtered_sentence)
def marks():
if request.method == 'POST':
f = request.files['userfile']
path = "./static/{}".format(f.filename)
f.save(path)
caption = caption_it.caption_this_image(path)
caption1 = "in the entered image " + caption
text_to_speech(caption1)
diction = {'image': path, 'caption': caption}
return render_template('index.html', your_result=diction)
def cap():
if request.method == 'POST':
f = request.files['userfile']
path = "./static/{}".format(f.filename)
f.save(path)
caption = caption_it.caption_this_image(path)
result_dic = {'image': path, 'caption': caption}
return render_template("index.html", your_result=result_dic)