Merge branch 'master' of https://github.com/shubham1172/VQA

Author: anujanegi

modules/answer_generator.py

@@ -1,13 +1,23 @@
+from deeppavlov import build_model, configs
+from utils.nostderrout import nostderrout
+
+
 class AnswerGenerator:
-    @staticmethod
-    def predict(comprehension, question):
+    def __init__(self):
+        """
+        create a model from pre-trained weights
+        """
+        print("START")
+        with nostderrout():
+            self.model = build_model(configs.squad.squad)
+        print("END")
+
+    def predict(self, comprehension, question):
         """
         predict answer for a question based on the given data
         :param comprehension: data to read for answering the question
         :param question: question based on the comprehension
         :return: answer for the question
         """
-        pass
+        return self.model([comprehension], [question])[0]
 
-ag = AnswerGenerator()
-print(ag.predict("There are two people.", "How many people are there?"))

requirements.txt

@@ -9,3 +9,4 @@ colorthief
 torch
 torchvision
 num2words
+deeppavlov

run.py

@@ -1,8 +1,9 @@
 import cv2
 import argparse
 import knowledge_graph
-import matplotlib.pyplot as plt
 from pprint import pprint
+from modules.answer_generator import AnswerGenerator
+from modules.paragraph_generator import ParagraphGenerator
 
 parser = argparse.ArgumentParser()
 parser.add_argument('-p', '--path', help='path of the input image', required=True)
@@ -13,5 +14,15 @@
 
 knowledge, frame = knowledge_graph.create_knowledge_graph(image)
 pprint(knowledge)
-plt.imshow(frame)
-plt.show()
+
+paragraph_generator = ParagraphGenerator()
+paragraph = paragraph_generator.generate(knowledge)
+
+answer_generator = AnswerGenerator()
+print(paragraph)
+
+while True:
+    question = input().strip()
+    if question == "":
+        break
+    print(answer_generator.predict(paragraph, question))

utils/nostderrout.py

@@ -0,0 +1,19 @@
+import contextlib
+import sys
+import os
+
+
+class DummyFile(object):
+    def write(self, x): pass
+
+
+@contextlib.contextmanager
+def nostderrout():
+    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+    save_stdout = sys.stdout
+    save_stderr = sys.stderr
+    sys.stdout = DummyFile()
+    sys.stderr = DummyFile()
+    yield
+    sys.stdout = save_stdout
+    sys.stderr = save_stderr