def post(self, request):
from aip import AipImageClassify
pic = request.FILES.get("pic")
if pic:
with open(
os.path.join(BASE_DIR,
"frontend/dist/static/media/land/%s") %
pic.name, 'wb') as f:
for chunk in pic.chunks():
f.write(chunk)
file_path1 = os.path.join(
BASE_DIR, "frontend/dist/static/media/land/%s") % pic.name
# print(file_path1)
""" 你的 APPID AK SK """
client = AipImageClassify(APP_ID_BAIDU, API_KEY_BAIDU,
SECRET_KEY_BAIDU)
""" 读取图片 """
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
image = get_file_content(file_path1)
""" 调用地标识别 """
try:
resp = client.landmark(image)
# print(resp['result']['landmark'])
# print(resp)
data = {"landmark": resp['result']['landmark']}
return JsonResponse(data=data,
json_dumps_params={'ensure_ascii': False})
except Exception as e:
return HttpResponse('请提交地标图片')
else:
return HttpResponse('请提交地标图片')
def BaiDu_image_recognize(file_path, recognize_type):
"""
图像识别
:param file_path: 文件路径
:param recognize_type: 识别类型，共12种：
1. 通用图像识别
2. 菜品识别
3. 车辆识别
4. logo商标识别
5. 动物识别
6. 植物识别
7. 图像主体检测
8. 地标识别
9. 食材识别
10. 红酒识别
11. 货币识别
:return:
"""
# TODO 隐私信息
""" 你的 APP_ID API_KEY SECRET_KEY """
app_id = '23899102' # '你的 App ID'
api_key = 'GKHIEq6gVOfp2AeRxfUopSDM' # '你的 Api Key'
secret_key = 'dLrlMlGemQ1oan2OS8GogLDD0dt1HuVI' # '你的 Secret Key'
# 获取百度云操作类对象
client = AipImageClassify(app_id, api_key, secret_key)
image = get_file_content(file_path)
# """ 调用通用物体识别 """
# result = client.dishDetect(image)
# print(result)
""" 如果有可选参数 """
options = {"baike_num": 5}
""" 带参数调用通用物体识别 """
if recognize_type == 1: # 通用图像识别
response = client.advancedGeneral(image, options)
elif recognize_type == 2: # 菜品识别
response = client.dishDetect(image, options)
elif recognize_type == 3: # 车辆识别
response = client.carDetect(image, options)
elif recognize_type == 4: # logo商标识别
response = client.logoSearch(image)
elif recognize_type == 5: # 动物识别
response = client.animalDetect(image, options)
elif recognize_type == 6: # 植物识别
response = client.plantDetect(image, options)
elif recognize_type == 7: # 图像主体检测
response = client.objectDetect(image)
elif recognize_type == 8: # 地标识别
response = client.landmark(image)
# 花卉识别已经移除
# elif recognize_type == 9: # 花卉识别
# response = client.flower(image)
elif recognize_type == 9: # 食材识别
response = client.ingredient(image, options)
elif recognize_type == 10: # 红酒识别
response = client.redwine(image)
elif recognize_type == 11: # 货币识别
response = client.currency(image)
else:
response = None
response = response['result'][0]
return response
class BaiduDetector(object):
def __init__(self, image_path):
self.image_path = image_path
self.image = get_file_content(image_path)
self.client = AipImageClassify(baidu_appid, baidu_apikey,
baidu_secretkey)
self.object_class = ''
self.object_classkeyword = ''
self.result_string = ''
self.cls_string = ''
self.object_keyword = ''
self.baike_des = ''
self.ignore_reply = 0
def config_result(self, result):
print('二级识别')
print(result)
result_arr = result['result']
self.object_keyword = '按照' + self.cls_string + '属性进行二级识别：'
for obj in result_arr:
probability = 0
if 'probability' in obj.keys():
probability = float(obj['probability'])
elif 'score' in obj.keys():
probability = float(obj['score'])
percent = probability * 100.0
if percent == 0:
self.object_keyword = self.object_keyword + '\n' + '可能是：' + obj[
'name']
else:
self.object_keyword = self.object_keyword + '\n' + str(
round(percent, 0)) + '%的可能是：' + obj['name']
# result_best = result_arr[0]
# self.object_keyword = result_best['name']
# baike_info = result_best['baike_info']
# self.baike_des = baike_info['description']
def label_detect(self, label, general_result):
result_arr = general_result['result']
result_best = result_arr[0]
if '车' in label:
print('车')
self.cls_string = '汽车'
result = self.client.carDetect(self.image)
self.config_result(result)
elif '食物' in label:
print('食物')
self.cls_string = '食物'
result = self.client.dishDetect(self.image)
self.config_result(result)
elif 'Logo' in label:
print('Logo')
self.cls_string = 'Logo'
result = self.client.logoSearch(self.image)
self.config_result(result)
elif '动物' in label:
print('动物')
self.cls_string = '动物'
result = self.client.animalDetect(self.image)
self.config_result(result)
elif '植物' in label:
print('植物')
self.cls_string = '植物'
result = self.client.plantDetect(self.image)
self.config_result(result)
elif '地标' in label or '建筑' in label:
print('地标')
self.cls_string = '地标'
result = self.client.landmark(self.image)
print('二级属性')
print(result)
self.object_keyword = ''
result_obj = result['result']
if (result_obj is list):
for obj in result_obj:
self.object_keyword = self.object_keyword + obj[
'landmark'] + '?'
elif (result_obj is dict):
self.object_keyword = self.object_keyword + result_obj[
'landmark'] + '?'
elif '人物' in label:
print('人物')
self.cls_string = '人物'
self.object_keyword = result_best['keyword']
else:
self.object_keyword = result_best['keyword']
def womengrade(self):
f = open("./react_words.json", encoding='utf-8')
map = json.load(f)
womengrade = map['womengrade']
index = random.randint(0, len(womengrade) - 1)
return womengrade[index]
def general_detect(self):
result = self.client.advancedGeneral(self.image)
print('通用识别')
print(result)
result_arr = result['result']
result_best = result_arr[0]
# baike_info = result_best['baike_info']
# self.baike_des = baike_info['description']
label_str = ''
result_str = '图像识别大类：'
self.ignore_reply = 0
for obj in result_arr:
#如果大于20%的几率是文字图，屏幕截图，不回答
score = float(obj['score'])
percent = score * 100.0
keyword = obj['keyword']
if percent > 20 and ('屏幕截图' in keyword or '文字图' in keyword):
self.ignore_reply = 1
result_str = result_str + '\n' + str(round(
percent, 0)) + '%的可能是：' + keyword + '(' + obj['root'] + ')'
label_str = label_str + obj['root'] + '?' + obj['keyword'] + '?'
print('label = ' + label_str)
if self.ignore_reply == 0:
self.result_string = result_str
self.object_class = result_best['root']
self.object_classkeyword = result_best['keyword']
self.label_detect(label_str, result)
else:
print('要忽略显示')
def answer(self):
if self.ignore_reply == 1:
return ''
cls_arr = self.object_class.split('-')
# 二级属性
second_att = ''
if self.object_keyword != '':
second_att = '\n' + self.object_keyword
# answer = '这是'+ self.object_classkeyword +'吧，一种' + cls_arr[len(cls_arr)-1] + second_att
answer = self.result_string + second_att
if '女人' in answer or '美女' in answer:
return self.womengrade()
else:
return answer
# if __name__ == '__main__':
# dectector = BaiduDetector('./car.jpeg')
# dectector.general_detect()
# print(dectector.object_class)
# print(dectector.object_classkeyword)
# print(dectector.object_keyword)
# print(dectector.baike_des)
from aip import AipImageClassify
""" 你的 APPID AK SK """
APP_ID = '16042058'
API_KEY = 'AyuLyqu4FNB4klZvGAHSjVaQ'
SECRET_KEY = 'MI53Tuf71Xt4KoQiqT7G3lUH96DC3mZ8'
client = AipImageClassify(APP_ID, API_KEY, SECRET_KEY)
""" 读取图片 """
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
image = get_file_content('/home/wy/Desktop/tiantan.jpg')
""" 调用地标识别 """
try:
resp = client.landmark(image)
print(resp['result']['landmark'])
except Exception as e:
print(e)
