def img2txt_ret():
# get_vecs_knn_ret(vecs_trans[0])
# get_feats_knn_ret(feats_trans[0])
search_id = request.args["id"]
print(search_id)
# run_vgg16(sess, search_id + ".jpg")
cat_id, imgs_id = get_feats_knn_ret(run_acmr(1, search_id))
categories_list = [
"art", "biology", "geography", "history", "literature", "media",
"music", "royalty", "sport", "warfare"
]
label = categories_list[cat_id - 1]
imgs = []
for img_id in imgs_id:
img = {}
temp_img = get_wikipedia_with_id(img_id)
img["id"] = temp_img.id
img["pic_id"] = temp_img.pic_id
img["name"] = temp_img.name
img["texts"] = temp_img.texts
imgs.append(img)
return render_template('img.html',
search_id=search_id,
label=label,
imgs=imgs,
categories_list=categories_list)
def txt2img_ret():
query_txt = request.args["query"]
if len(query_txt) > 0:
cat_id, imgs_id = get_vecs_knn_ret(run_acmr(0,
extract_text(query_txt)))
# import numpy as np
# cat_id, imgs_id = get_vecs_knn_ret(np.fromstring(get_wikipedia_with_id(20).vecs, np.float32))
categories_list = [
"art", "biology", "geography", "history", "literature", "media",
"music", "royalty", "sport", "warfare"
]
label = categories_list[cat_id - 1]
imgs = []
for img_id in imgs_id:
img = {}
temp_img = get_wikipedia_with_id(img_id)
img["id"] = temp_img.id
img["pic_id"] = temp_img.pic_id
img["name"] = temp_img.name
img["texts"] = temp_img.texts
imgs.append(img)
return render_template('text.html',
query_txt=query_txt,
label=label,
imgs=imgs,
categories_list=categories_list)
else:
return make_response("异常输入～")
def detail(id):
pedia = get_wikipedia_with_id(id)
return render_template("detail.html",
name=pedia.name,
texts=pedia.texts,
pic_id=pedia.pic_id)