我正试图通过关注Google's tutorial使用云视觉API来测试谷歌云视觉API。
步骤1：通过在终端中键入以下命令来生成JSON请求
$ python path/to/generate_json.py -i path/to/cloudVisionInputFile -o path/to/request.json
以上命令生成request.json文件。
第2步：使用Curl发送生成的请求
$ curl -v -k -s -H "Content-Type: application/json" https://vision.googleapis.com/v1/images:annotate?key=AIzaSyD7Pm-ebpjas62ihvp9v1gAhTk --data-binary @/path/to/request.json > result.json
终端输出（步骤2之后）
请注意，终端中的输出（见下文）显示Content-Length: 0和[data not shown]。
有人可以告诉为什么内容长度为零？以及为什么我无法从谷歌云视觉api获得JSON响应？
以下是终端输出
* Hostname was NOT found in DNS cache
* Trying 216.58.347.74...
* Connected to vision.googleapis.com (216.58.347.74) port 443 (#0)
* successfully set certificate verify locations:
* CAfile: /opt/local/share/curl/curl-ca-bundle.crt
CApath: none
* SSLv3, TLS handshake, Client hello (1):
} [data not shown]
* SSLv3, TLS handshake, Server hello (2):
{ [data not shown]
* SSLv3, TLS handshake, CERT (11):
{ [data not shown]
* SSLv3, TLS handshake, Server key exchange (12):
{ [data not shown]
* SSLv3, TLS handshake, Server finished (14):
{ [data not shown]
* SSLv3, TLS handshake, Client key exchange (16):
} [data not shown]
* SSLv3, TLS change cipher, Client hello (1):
} [data not shown]
* SSLv3, TLS handshake, Finished (20):
} [data not shown]
* SSLv3, TLS change cipher, Client hello (1):
{ [data not shown]
* SSLv3, TLS handshake, Finished (20):
{ [data not shown]
* SSL connection using TLSv1.2 / ECDHE-RSA-AES128-GCM-SHA256
* Server certificate:
* subject: C=US; ST=California; L=Mountain View; O=Google Inc; CN=*.googleapis.com
* start date: 2016-10-06 12:44:36 GMT
* expire date: 2016-12-29 12:28:00 GMT
* issuer: C=US; O=Google Inc; CN=Google Internet Authority G2
* SSL certificate verify ok.
> POST /v1/images:annotate?key=AIzaSyD7Pm-ebpjas62ihvp9v1gAhTk HTTP/1.1
> User-Agent: curl/7.37.1
> Host: vision.googleapis.com
> Accept: */*
> Content-Type: application/json
> Content-Length: 0
>
< HTTP/1.1 200 OK
< Content-Type: application/json; charset=UTF-8
< Vary: X-Origin
< Vary: Referer
< Date: Mon, 17 Oct 2016 13:02:56 GMT
* Server ESF is not blacklisted
< Server: ESF
< Cache-Control: private
< X-XSS-Protection: 1; mode=block
< X-Frame-Options: SAMEORIGIN
< X-Content-Type-Options: nosniff
< Alt-Svc: quic=":443"; ma=2592000; v="36,35,34,33,32"
< Accept-Ranges: none
< Vary: Origin,Accept-Encoding
< Transfer-Encoding: chunked
<
{ [data not shown]
* Connection #0 to host vision.googleapis.com left intact
以下是request.json文件中生成的JSON请求
{
"requests": [{
"image": {
"content": "/9j/4AAQSkZJRgABAQAA..."
},
"features": [{
"type": "TYPE_UNSPECIFIED",
"maxResults": 10
}, {
"type": "FACE_DETECTION",
"maxResults": 10
}, {
"type": "LANDMARK_DETECTION",
"maxResults": 10
}, {
"type": "LOGO_DETECTION",
"maxResults": 10
}, {
"type": "LABEL_DETECTION",
"maxResults": 10
}, {
"type": "TEXT_DETECTION",
"maxResults": 10
}, {
"type": "SAFE_SEARCH_DETECTION",
"maxResults": 10
}]
}, {
"image": {
"content": "/9j/4AAQSkZJRgABAQAAAQABAAD..."
},
"features": [{
"type": "TYPE_UNSPECIFIED",
"maxResults": 10
}, {
"type": "FACE_DETECTION",
"maxResults": 10
}, {
"type": "LANDMARK_DETECTION",
"maxResults": 10
}, {
"type": "LOGO_DETECTION",
"maxResults": 10
}, {
"type": "LABEL_DETECTION",
"maxResults": 10
}, {
"type": "TEXT_DETECTION",
"maxResults": 10
}, {
"type": "SAFE_SEARCH_DETECTION",
"maxResults": 10
}]
}]
}
以下是generate_json.py
import argparse
import base64
import json
import sys
def main(cloudVisionInputFile, request):
"""Translates the input file into a json output file.
Args:
input_file: a file object, containing lines of input to convert.
output_filename: the name of the file to output the json to.
"""
# Collect all requests into an array - one per line in the input file
request_list = []
for line in input_file:
# The first value of a line is the image. The rest are features.
image_filename, features = line.lstrip().split(' ', 1)
# First, get the image data
with open(image_filename, 'rb') as image_file:
content_json_obj = {
'content': base64.b64encode(image_file.read()).decode('UTF-8')
}
# Then parse out all the features we want to compute on this image
feature_json_obj = []
for word in features.split(' '):
feature, max_results = word.split(':', 1)
feature_json_obj.append({
'type': get_detection_type(feature),
'maxResults': int(max_results),
})
# Now add it to the request
request_list.append({
'features': feature_json_obj,
'image': content_json_obj,
})
# Write the object to a file, as json
# with open(output_filename, 'w') as output_file:
with open(request, 'w') as output_file:
json.dump({'requests': request_list}, output_file)
DETECTION_TYPES = [
'TYPE_UNSPECIFIED',
'FACE_DETECTION',
'LANDMARK_DETECTION',
'LOGO_DETECTION',
'LABEL_DETECTION',
'TEXT_DETECTION',
'SAFE_SEARCH_DETECTION',
]
def get_detection_type(detect_num):
"""Return the Vision API symbol corresponding to the given number."""
detect_num = int(detect_num)
if 0 < detect_num < len(DETECTION_TYPES):
return DETECTION_TYPES[detect_num]
else:
return DETECTION_TYPES[0]
# [END generate_json]
FILE_FORMAT_DESCRIPTION = '''
Each line in the input file must be of the form:
file_path feature:max_results feature:max_results ....
where 'file_path' is the path to the image file you'd like
to annotate, 'feature' is a number from 1 to %s,
corresponding to the feature to detect, and max_results is a
number specifying the maximum number of those features to
detect.
The valid values - and their corresponding meanings - for
'feature' are:
%s
'''.strip() % (
len(DETECTION_TYPES) - 1,
# The numbered list of detection types
'\n '.join(
# Don't present the 0th detection type ('UNSPECIFIED') as an option.
'%s: %s' % (i + 1, detection_type)
for i, detection_type in enumerate(DETECTION_TYPES[1:])))
if __name__ == '__main__':
parser = argparse.ArgumentParser(
formatter_class=argparse.RawTextHelpFormatter
)
parser.add_argument(
'-i', dest='input_file', required=True,
help='The input file to convert to json.\n' + FILE_FORMAT_DESCRIPTION)
parser.add_argument(
'-o', dest='output_file', required=True,
help='The name of the json file to output to.')
args = parser.parse_args()
try:
with open(args.input_file, 'r') as input_file:
main(input_file, args.output_file)
except ValueError as e:
sys.exit('Invalid input file format.\n' + FILE_FORMAT_DESCRIPTION)
以下是cloudVisionInputFile中的文字
/Users/pravishanthmadepally/documents/machineLearning/googleCloudVisionAPI/images/img1.jpeg 0:10 1:10 2:10 3:10 4:10 5:10 6:10
/Users/pravishanthmadepally/documents/machineLearning/googleCloudVisionAPI/images/img2.jpeg 0:10 1:10 2:10 3:10 4:10 5:10 6:10
答案 0 :(得分：0)
我只是尝试使用以下步骤复制您的问题：
这是我的输出
* STATE: INIT => CONNECT handle 0x600080a40; line 1397 (connection #-5000)
* Added connection 0. The cache now contains 1 members
* Trying 66.102.1.95...
* TCP_NODELAY set
* STATE: CONNECT => WAITCONNECT handle 0x600080a40; line 1450 (connection #0)
* Connected to vision.googleapis.com (66.102.1.95) port 443 (#0)
* STATE: WAITCONNECT => SENDPROTOCONNECT handle 0x600080a40; line 1557 (connection #0)
* Marked for [keep alive]: HTTP default
* ALPN, offering h2
* ALPN, offering http/1.1
* Cipher selection: ALL:!EXPORT:!EXPORT40:!EXPORT56:!aNULL:!LOW:!RC4:@STRENGTH
* successfully set certificate verify locations:
* CAfile: /etc/pki/tls/certs/ca-bundle.crt
CApath: none
* TLSv1.2 (OUT), TLS header, Certificate Status (22):
* TLSv1.2 (OUT), TLS handshake, Client hello (1):
* STATE: SENDPROTOCONNECT => PROTOCONNECT handle 0x600080a40; line 1571 (connection #0)
* TLSv1.2 (IN), TLS handshake, Server hello (2):
* TLSv1.2 (IN), TLS handshake, Certificate (11):
* TLSv1.2 (IN), TLS handshake, Server key exchange (12):
* TLSv1.2 (IN), TLS handshake, Server finished (14):
* TLSv1.2 (OUT), TLS handshake, Client key exchange (16):
* TLSv1.2 (OUT), TLS change cipher, Client hello (1):
* TLSv1.2 (OUT), TLS handshake, Finished (20):
* TLSv1.2 (IN), TLS change cipher, Client hello (1):
* TLSv1.2 (IN), TLS handshake, Finished (20):
* SSL connection using TLSv1.2 / ECDHE-RSA-AES128-GCM-SHA256
* ALPN, server accepted to use h2
* Server certificate:
* subject: C=US; ST=California; L=Mountain View; O=Google Inc; CN=*.googleapis.com
* start date: Oct 6 12:44:36 2016 GMT
* expire date: Dec 29 12:28:00 2016 GMT
* issuer: C=US; O=Google Inc; CN=Google Internet Authority G2
* SSL certificate verify ok.
* STATE: PROTOCONNECT => DO handle 0x600080a40; line 1592 (connection #0)
* Using HTTP2, server supports multi-use
* Connection state changed (HTTP/2 confirmed)
* Copying HTTP/2 data in stream buffer to connection buffer after upgrade: len=0
* nghttp2_session_mem_recv() returns 0
* http2_send len=203
* Using Stream ID: 1 (easy handle 0x600080a40)
* before_frame_send() was called
* on_frame_send() was called, length = 106
> POST /v1/images:annotate?key=AIzaSyBj4XkAmOPByBmNbrcBJT0KBMM6xAw7eAM HTTP/1.1
> Host: vision.googleapis.com
> User-Agent: curl/7.50.3
> Accept: */*
> Content-Type: application/json
> Content-Length: 27170
>
* STATE: DO => DO_DONE handle 0x600080a40; line 1654 (connection #0)
* multi changed, check CONNECT_PEND queue!
* STATE: DO_DONE => WAITPERFORM handle 0x600080a40; line 1781 (connection #0)
* STATE: WAITPERFORM => PERFORM handle 0x600080a40; line 1791 (connection #0)
* http2_recv: easy 0x600080a40 (stream 1)
* nread=27
* Got SETTINGS
* MAX_CONCURRENT_STREAMS == 100
* ENABLE_PUSH == TRUE
* Connection state changed (MAX_CONCURRENT_STREAMS updated)!
* nghttp2_session_mem_recv() returns 27
* All data in connection buffer processed
* http2_recv returns AGAIN for stream 1
* http2_send len=16384
* data_source_read_callback: returns 16384 bytes stream 1
* on_frame_send() was called, length = 16384
* http2_send returns 16384 for stream 1
* multi changed, check CONNECT_PEND queue!
* http2_recv: easy 0x600080a40 (stream 1)
* nread=13
* nghttp2_session_mem_recv() returns 13
* All data in connection buffer processed
* http2_recv returns AGAIN for stream 1
* http2_send len=10786
* data_source_read_callback: returns 10786 bytes stream 1
* on_frame_send() was called, length = 10786
* http2_send returns 10786 for stream 1
* We are completely uploaded and fine
* http2_recv: easy 0x600080a40 (stream 1)
* nread=9
* Got SETTINGS
* MAX_CONCURRENT_STREAMS == 100
* ENABLE_PUSH == TRUE
* nghttp2_session_mem_recv() returns 9
* All data in connection buffer processed
* http2_recv returns AGAIN for stream 1
* http2_recv: easy 0x600080a40 (stream 1)
* nread=225
* on_begin_headers() was called
* h2 status: HTTP/2 200 (easy 0x600080a40)
* h2 header: content-type: application/json; charset=UTF-8
* h2 header: vary: X-Origin
* h2 header: vary: Referer
* h2 header: vary: Origin,Accept-Encoding
* h2 header: date: Mon, 17 Oct 2016 14:27:59 GMT
* h2 header: server: ESF
* h2 header: cache-control: private
* h2 header: x-xss-protection: 1; mode=block
* h2 header: x-frame-options: SAMEORIGIN
* h2 header: x-content-type-options: nosniff
* h2 header: alt-svc: quic=":443"; ma=2592000; v="36,35,34,33,32"
* h2 header: accept-ranges: none
* on_frame_recv() header 1 stream 1
* Store 367 bytes headers from stream 1 at 0x600081410
* nghttp2_session_mem_recv() returns 225
* All data in connection buffer processed
* http2_recv: returns 367 for stream 1
* HTTP/2 found, allow multiplexing
< HTTP/2 200
< content-type: application/json; charset=UTF-8
< vary: X-Origin
< vary: Referer
< vary: Origin,Accept-Encoding
< date: Mon, 17 Oct 2016 14:27:59 GMT
< server: ESF
< cache-control: private
< x-xss-protection: 1; mode=block
< x-frame-options: SAMEORIGIN
< x-content-type-options: nosniff
< alt-svc: quic=":443"; ma=2592000; v="36,35,34,33,32"
< accept-ranges: none
<
* http2_recv: easy 0x600080a40 (stream 1)
* nread=1401
* 1392 data received for stream 1 (14992 left in buffer 0x600081410, total 1392)
* nghttp2_session_mem_recv() returns 1401
* All data in connection buffer processed
* http2_recv: returns 1392 for stream 1
{
"responses": [
{
"labelAnnotations": [
{
"mid": "/m/07s6nbt",
"description": "text",
"score": 0.941945
},
{
"mid": "/m/03gq5hm",
"description": "font",
"score": 0.87127215
},
{
"mid": "/m/03scnj",
"description": "line",
"score": 0.72790623
},
{
"mid": "/m/01cd9",
你可以看到它工作正常！ 你的--data-binary @ / path / to / request.json参数在你执行时是如何看起来的？
答案 1 :(得分：0)
如果您尝试使用Python中的Cloud Vision API，可能需要尝试使用google.cloud client library。
要使用正确的范围进行身份验证，您需要在云控制台中生成服务帐户，并从您的代码（或环境变量）指向该帐户。有关详细信息，请参阅the Vision auth section：
从credentials manager获取服务帐户，然后指向您环境中的项目和JSON凭据文件：
$ export GOOGLE_CLOUD_PROJECT="your-project-id-here"
$ export GOOGLE_APPLICATION_CREDENTIALS="/path/to/keyfile.json"
您可以进行手动检测，就像您在问题中所显示的那样（指定要检测的不同内容），如下所示：
>>> from google.cloud import vision
>>> from google.cloud.vision.feature import Feature
>>> from google.cloud.vision.feature import FeatureTypes
>>> client = vision.Client()
>>> image = client.image(source_uri='gs://my-test-bucket/image.jpg')
>>> features = [Feature(FeatureTypes.FACE_DETECTION, 5),
... Feature(FeatureTypes.LOGO_DETECTION, 3)]
>>> annotations = image.detect(features)
>>> len(annotations)
2
>>> for face in annotations[0].faces:
... print(face.joy)
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
>>> for logo in annotations[0].logos:
... print(logo.description)
'google'
'github'
（有关详细信息，请参阅https://googlecloudplatform.github.io/google-cloud-python/stable/vision-usage.html#manual-detection。）
但是，如果您只寻找一件事（例如标签），则可以使用特定于功能的检测：
>>> from google.cloud import vision
>>> client = vision.Client()
>>> image = client.image(source_uri='gs://my-storage-bucket/image.jpg')
>>> labels = image.detect_labels(limit=3)
>>> labels[0].description
'automobile'
>>> labels[0].score
0.9863683