def exe_test(sess, data, batch_size, v2i, i2v, hf, feature_shape,
predict_words, input_video, input_captions, y, finished_beam, logprobs_finished_beams, past_logprobs, beam_hidden_state, past_symbols_states, finished_beams_states, capl=16):
caption_output = []
total_data = len(data)
num_batch = int(round(total_data*1.0/batch_size))
for batch_idx in xrange(num_batch):
batch_caption = data[batch_idx*batch_size:min((batch_idx+1)*batch_size,total_data)]
data_v = MsrDataUtil.getBatchVideoFeature(batch_caption,hf,feature_shape)
data_c, data_y = MsrDataUtil.getBatchTestCaption(batch_caption, v2i, capl=capl)
[gw,tw,gp, gl, pp, pss, fbs] = sess.run([finished_beam, predict_words, logprobs_finished_beams, past_logprobs, beam_hidden_state, past_symbols_states, finished_beams_states],feed_dict={input_video:data_v, input_captions:data_c, y:data_y})
generated_captions = MsrDataUtil.convertCaptionI2V(batch_caption, gw, i2v)
for idx, sen in enumerate(generated_captions):
# print(gw[idx])
print('%s : %s' %(batch_caption[idx].keys()[0],sen))
# print(pss)
# print(fbs)
# print(gp)
# print(gl)
# print(pp)
caption_output.append({'image_id':batch_caption[idx].keys()[0],'caption':sen})
js = {}
js['val_predictions'] = caption_output
return js
def exe_test(sess,
data,
batch_size,
v2i,
i2v,
hf,
feature_shape,
predict_words,
input_video,
input_captions,
y,
predict_words2,
capl=16):
caption_output = []
total_data = len(data)
num_batch = int(round(total_data * 1.0 / batch_size))
for batch_idx in xrange(num_batch):
batch_caption = data[batch_idx *
batch_size:min((batch_idx + 1) *
batch_size, total_data)]
data_v = MsrDataUtil.getBatchVideoFeature(batch_caption, hf,
feature_shape)
data_c, data_y = MsrDataUtil.getBatchTestCaption(batch_caption,
v2i,
capl=capl)
[gw, tw] = sess.run([predict_words, predict_words2],
feed_dict={
input_video: data_v,
input_captions: data_c,
y: data_y
})
# print(gw)
# print(tp)
# print(atp)
generated_captions = MsrDataUtil.convertCaptionI2V(
batch_caption, gw, i2v)
for idx, sen in enumerate(generated_captions):
print('%s : %s' % (batch_caption[idx].keys()[0], sen))
caption_output.append({
'image_id': batch_caption[idx].keys()[0],
'caption': sen
})
js = {}
js['val_predictions'] = caption_output
return js
