def captionImage(url):
image_url = url
cBot = CaptionBot()
caption = cBot.url_caption(image_url)
caption = caption.split(" ")[2:]
caption = " ".join(caption)
return caption
def describe():
msgtype = request.form['type']
##question=request.form['question']
print(str(msgtype) + "is message ")
imagefile = request.files['imagefile']
filename = secure_filename(imagefile.filename)
imagefile.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
print(filename)
filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
print(filepath)
if (msgtype == '1'):
c = CaptionBot()
print("caption bot running")
result = c.file_caption(filepath)
print(result)
return jsonify({
'message': result,
'type': msgtype,
'filename': filename,
'filepath': filepath
})
elif (msgtype == '2'):
question = request.form['question']
##establish connection
##if (question is None) return jsonify({'message':'error , didnt include question','type':'2'})
response = requests.get(url, headers=header)
##upload image
url1 = 'http://vqa.daylen.com/api/upload_image'
files = {'file': open(filepath, 'rb')}
response = requests.post(url1, files=files, headers=header)
data = json.loads(response.text)
im_id = data['img_id']
print im_id
## upload question
url2 = 'http://vqa.daylen.com/api/upload_question'
#'fa10956c0743670ec5c924ce1523ab16'
datas = {'img_id': im_id, 'question': question}
response = requests.post(url2, data=datas, headers=header)
##get response
print(response.text)
data = json.loads(response.text)
return jsonify({'message': data[u'answer'], 'type': '2'})
else:
return jsonify({'message': 'error in type ', 'type': '1'})
def captioning(video_id, scenes):
print('Captioning {}'.format(video_id))
start_time = datetime.now()
c = CaptionBot()
result = []
cached_path = 'cached/{}.data'.format(video_id)
if os.path.isfile(cached_path):
with open(cached_path, 'rb') as cached_file:
result = pickle.load(cached_file)
for x in result:
print('At {}: {}'.format(int(x['start_time']), x['caption']))
else:
for x in scenes:
caption = c.file_caption(x[0])
print('At {}: {}'.format(int(x[1]), caption))
result.append({'start_time': x[1], 'caption': caption})
with open(cached_path, 'wb') as cached_file:
pickle.dump(result, cached_file)
print('Captioning: {} seconds'.format(datetime.now() - start_time))
return result
class Captioner:
def __init__(self):
self.caption_bot = CaptionBot()
self.prev_caption = ''
def caption_img(self, frame, get_prev=False):
if not get_prev:
img_name = 'to_caption.jpg'
cv2.imwrite(img_name, frame)
caption = self.caption_bot.file_caption(img_name)
self.prev_caption = caption
return self.prev_caption
def getDescription():
if request.method == "POST":
img = request.data[5:]
data = img
c = CaptionBot()
caption = c.url_caption(str(data))
r = {"success":caption}
lines = getText(str(data))
text = ""
if lines:
text = parseText(lines)
if text:
response = {"success":text}
return json.dumps(response)
aux = "this image has the following text: " + text
response = {"success" : aux}
return json.dumps(response)
try:
conn = httplib.HTTPSConnection('westus.api.cognitive.microsoft.com')
body = {"url":data}
conn.request("POST", "/face/v1.0/detect?%s" % params, json.dumps(body), headers)
response = conn.getresponse()
data = response.read()
data = json.loads(data)
if(data):
age = data[0]["faceAttributes"]["age"]
gender = data[0]["faceAttributes"]["gender"]
moustache = data[0]["faceAttributes"]["facialHair"]["moustache"]
beard = data[0]["faceAttributes"]["facialHair"]["beard"]
glasses = data[0]["faceAttributes"]["glasses"]
description = " It's gender is " + gender + " with an age of " + str(age) + " years. It has a "+str(100*float(moustache)) +" percent probability of having a moustache and "+str(100*float(beard))+" percent probability of having a beard. He has "+glasses
r["success"] += description
conn.close()
except Exception as e:
print(e)
return json.dumps(r)
class ImageDescriber:
def __init__(self):
self.captionBot = CaptionBot() #www.captionbot.ai
self.translator = Translator()
self.dest = 'ru'
self.description = 'send_photo - Я могу рассказать, что изображено на картинке \n'
def describeImg(self, bot, update):
imgId = update.message.photo[-1]
imgPath = bot.getFile(imgId)
imgPath = imgPath['file_path']
caption = self.getImageCaption(imgPath)
bot.send_message(chat_id=update.message.chat_id, text=caption)
def getImageCaption(self, imgPath):
caption = self.captionBot.url_caption(imgPath)
caption = self.translator.translate(caption, dest=self.dest).text
return caption
# -*- coding: utf-8 -*-
import sys
from captionbot import CaptionBot
import emoji
# create instance of CaptionBot
c = CaptionBot()
for line in open('all_scrapes.csv'):
line = line.rstrip()
cols = line.split(',')
img_url = cols[0]
# if line is the header
if img_url == 'img_url':
print(line)
continue
#------------- Clean Image URL -------------#
# remove quotes from img_url
img_url = img_url[1:-1]
caption = cols[1]
#--------- Clean Instagram Caption ---------#
# if there is no caption skip it
if len(caption) < 1: continue
# currently emojis look like (apparently called mojibake): 😘
# should turn emojis into actual emojis
#caption.encode('cp1252').decode('utf-8')
# now try converting emojis to aliases
try:
from captionbot import CaptionBot
c = CaptionBot()
#msg = c.url_caption("https://beebom-redkapmedia.netdna-ssl.com/wp-content/uploads/2016/01/Reverse-Image-Search-Engines-Apps-And-Its-Uses-2016.jpg")
#msg2 = c.url_caption("https://upload.wikimedia.org/wikipedia/commons/thumb/6/63/Collection_of_military_aircraft.jpg/1200px-Collection_of_military_aircraft.jpg")
msg2 = c.file_caption("/Users/khanh/Desktop/bbb.jpg")
print(msg2)
import cv2
from captionbot import CaptionBot
c = CaptionBot()
cap = cv2.VideoCapture(0)
while True:
r, f = cap.read()
if r == True:
cv2.imshow("Stream", f)
key = cv2.waitKey(1)
if key == ord('a'):
print("Generating Caption...")
cv2.imwrite('image.jpg', f)
caption = c.file_caption('/home/aditya/Hack-a-bit2019/' +
'image.jpg')
print(caption)
elif key == 27:
break
else:
continue
cv2.destroyAllWindows()
cap.release()
import os
import time
import tarfile
import glob
import six.moves.urllib as urllib
import cv2
from tqdm import tqdm
import numpy as np
import tensorflow as tf
from ssd_mobilenet_utils import *
from captionbot import CaptionBot
c = CaptionBot()
def run_detection(image, interpreter):
interpreter.set_tensor(input_details[0]['index'], image)
interpreter.invoke()
boxes = interpreter.get_tensor(output_details[0]['index'])
classes = interpreter.get_tensor(output_details[1]['index'])
scores = interpreter.get_tensor(output_details[2]['index'])
num = interpreter.get_tensor(output_details[3]['index'])
boxes, scores, classes = np.squeeze(boxes), np.squeeze(scores), np.squeeze(
classes + 1).astype(np.int32)
out_scores, out_boxes, out_classes = non_max_suppression(
scores, boxes, classes)
# Print predictions info
#print('Found {} boxes for {}'.format(len(out_boxes), 'images/dog.jpg'))
def __init__(self):
self.captionBot = CaptionBot() #www.captionbot.ai
self.translator = Translator()
self.dest = 'ru'
self.description = 'send_photo - Я могу рассказать, что изображено на картинке \n'
def __init__(self):
self.caption_bot = CaptionBot()
self.prev_caption = ''
import os
import json
from captionbot import CaptionBot
import requests
from requests.packages.urllib3.exceptions import InsecureRequestWarning
from requests.packages.urllib3.exceptions import InsecurePlatformWarning
requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
requests.packages.urllib3.disable_warnings(InsecurePlatformWarning)
c = CaptionBot()
json_object = {'data': {'caption': "", 'filename': "", 'film-frame': 0}}
fps = 25
stepInSeconds = 3
stepInFrames = fps * stepInSeconds
frame_files = 0
json_files = 0
for f in os.listdir('data/frames/'):
parsed = f.split(".")
if parsed[1] == 'png':
frame_files += 1
else:
json_files += 1
index = json_files + 1
print "Total frames:", str(frame_files)
def captionimage(url):
c = CaptionBot()
return c.url_caption(url)
