I am a Java developer and I have couple of questions related to Google speech API V1Beta1.
Question1 (Syncrecognize case):
I tried to upload (through GCS) small size (less than one min running file) audio file to google speech api it is working But the confidence output level is 0.32497215 only. That is my result is not exactly same to my audio input.
How to increase the confidence level output?
Question 2 (Asyncrecognize case):
I tried big size audio file (more than one min running file). This case I used the API call:
https://speech.googleapis.com/v1beta1/speech:asyncrecognize?key=XXXXXXXXXXXXXXXXXXXX
and Payload:
"{"config":{"encoding":"LINEAR16","sample_rate": 16000},"audio":{"uri":"gs://" + bucketName +"/"+ objectName + ""}}"
Here I got the output json like
{"name": "57...........................95"}.
After getting this output I make new API call (Operation interface) with this name value.
https://speech.googleapis.com/v1beta1/operations/57.................................95?key=XXXXXXXXXXXXXXXXX
I got the output
{
"name": "57....................................95",
"done": true,
"response": {
"#type": "type.googleapis.com/google.cloud.speech.v1beta1.AsyncRecognizeResponse"
}
}
How to proceed the work with this value? I need to get audio speech text.
Please help me to fix this issues. Thanks in advance.
Ideas to Question 1:
You should give more details in RecognitionConfig object, for example specify the languageCode and add hints via the SpeechContext object.
Answer to Question 2:
Check the sample rate of the audio file, you must be sure that is equal to the rate you gave in the request. You can check it e.g. with the following code soxi audio_file.flac (sox needed for this one).
Related
I cant find the solution anywhere and mine doesn't seem to work.
I just want to see the last plate string in the browser,or the few last plates,doesn't matter.
http://login:password#MY.IP/ISAPI/Traffic/channels/1/vehicleDetect/plates/
<AfterTime><picTime>2021-12-09T09:07:15Z</picTime></AfterTime>
I do have a plate taken exactly at the time im using in pictime,but the result im getting is;
This XML file does not appear to have any style information associated with it. The document tree is shown below.
<ResponseStatus xmlns="
http://www.hikvision.com/ver20/XMLSchema
" version="2.0">
<requestURL>
/ISAPI/Traffic/channels/1/vehicleDetect/plates/
<AfterTime>
<picTime>2021-12-09T09:01:15Z</picTime>
</AfterTime>
</requestURL>
<statusCode>4</statusCode>
<statusString>Invalid Operation</statusString>
<subStatusCode>invalidOperation</subStatusCode>
</ResponseStatus>
POSTMAN
Edit:
Are you certain that the ISAPI setting is enabled in the camera configuration?
It's not possible in the browser without some tool to send and process your API request.
Have you tried using Postman?
Don't forget to use a Digest Auth header.
from requests.auth import HTTPDigestAuth
import requests
url = 'http://<Your IP>/ISAPI/Traffic/channels/1/vehicleDetect/plates/'
data = "<AfterTime><picTime>20220912T192011+0400</picTime></AfterTime>"
r=requests.get(url, data =data,auth=HTTPDigestAuth('admin', 'password'))
print(r.text)
Try this one after enabling this setting in camera
Screenshot
Currently I'm using form recognizer version 2.1 preview to train a custom model. I'm able to test the model in Form Recognizer Labeling Tool and got the output. When I input the same file that I got out in labeling tool in my program I'm getting the error below.
{"status": "failed", "createdDateTime": "2020-09-25T20:03:21Z", "lastUpdatedDateTime": "2020-09-25T20:03:21Z", "analyzeResult": {"version": "2.1.0", "errors": [{"code": "2005", "message": "The file submitted couldn't be parsed. This can be due to one of the following reasons: the file format is not supported ( Supported formats include JPEG, PNG, BMP, PDF and TIFF), the file is corrupted or password protected."}]}}
The GET request code used is:
resp = requests.get(url=get_url,headers={"Ocp-Apim-Subscription-Key":FORM_RECOGNIZER_SUBSCRIPTION_KEY})
I have saved the file to server and then tried to read it from there and pass the read file to form recognizer. This worked for me. But I don't know why did it happen.
I also encountered this exact error message following this article.
The article show 4 steps:
Train Model (require SAS to blob - whole folder)
Get model result
Analyze (require SAS to a single file)
Get analyze result
Profit
I got this error on step 4.
After monkeying around, I figured that the cause is not actually in step 4 but in step 3 instead. I was providing SAS to the blob instead of SAS to the file.
After I corrected the SAS URL it works perfectly.
Here is how to get SAS to blob:
Here is how to get SAS to a file:
What file are you trying to use as input ? Form Recognizer supports PDF, Tiff and images (PNG and JPEG) as file types and inputs to the analyze API. See more details here - https://learn.microsoft.com/en-us/azure/cognitive-services/form-recognizer/quickstarts/python-labeled-data?tabs=v2-0#analyze-forms-for-key-value-pairs-and-tables
Scenario: I've been stuck on this for way to long and I think solution might be easy but I just can't see it, this is the scenario:
cURL POST to http://localhost:8080/my_imports (raw JSON data on body)
->
MyImportsCustomHandler (extends ThreadedHttpRequestHandler [Validations]
->
MyObjectProcessor (extends Processor) [JSON deserialize and data massage]
->
MyFirstDocumentProcessor (extends DocumentProcessor) [Set some fields and save]
Problem is that execution never reaches MyFirstDocumentProcessor, likely because request didn't started from the document_api endpoints (intentionaly).
There are no errors thrown, just processing route never reaches the document processor chain, I think it should because on MyObjectProcessor I'm doing:
DocumentType type =
localDocHandler.getDocumentTypeManager().getDocumentType("my_doc");
DocumentId id = new DocumentId("id:default:my_doc::2");
Document document = new Document(type, id);
DocumentPut docPut = new DocumentPut(document);
Processing proc = com.yahoo.docproc.Processing.of(docPut);
I got this idea from here: https://github.com/vespa-engine/vespa/blob/master/docproc/src/test/java/com/yahoo/docproc/util/SplitterJoinerTestCase.java
but on that test I see this line splitter.process(p);, which I'm not able to find a suitable replacement that works inside a Processor, in that context I only have the Request, Execution and DocumentProcessingHandler
I hope somebody versed on Vespa con shine some light on this, is just the last hop on the processing chain that I can't bridge :|
To write documents from Java code, you need to use the Document Access API:
http://docs.vespa.ai/documentation/document-api-guide.html#document-access
A working solution is in https://github.com/vespa-engine/sample-apps/pull/44
I'm working with this list videos example for GAE and if you try to run it on that page you can see that there's no next_page_token
I've even tried to self.response.out.write(next_page_token) and got None.
For example purposes I've submitted Channel name to be Google (which surely has more than 50 videos). I only get 50, no token that I can see, no pagination indication or anything like that.
What am I missing here?
Please advise,
Thanks a lot
Here is the first request pre-filled for you. Click execute at the bottom:
https://developers.google.com/apis-explorer/#p/youtube/v3/youtube.channels.list?part=snippet%252CcontentDetails&forUsername=Google&_h=1&
Following that result and hitting the next api in the code,
https://developers.google.com/apis-explorer/#p/youtube/v3/youtube.playlistItems.list?part=snippet&maxResults=50&playlistId=UUK8sQmJBp8GCxrOtXWBpyEA&_h=3&
Clicking execute on that shows that nextPageToken set. Either the code example from Google has a bug in it, or it is a copy paste error somewhere.
EDIT:
There is a bug in the code sample provided.
playlistitems_response looks similar to this:
{
"kind": "youtube#playlistItemListResponse",
"etag": "\"eYE31WLho912TfxEBDDRSwEQ5Ms/vUtg-sAFafmsExy-5XOvaMIfVN0\"",
"nextPageToken": "CDQQAA",
"prevPageToken": "CDIQAQ",
"pageInfo": {
"totalResults": 1634,
"resultsPerPage": 2
},
"items": [{...}]
}
The nextPageToken is being extracted like playlistitems_response.get('tokenPagination', {}).get('nextPageToken') when it
should read playlistitems_response.get('nextPageToken').
I recently started using bottle and GAE blobstore and while I can upload the files to the blobstore I cannot seem to find a way to download them from the store.
I followed the examples from the documentation but was only successful on the uploading part. I cannot integrate the example in my app since I'm using a different framework from webapp/2.
How would I go about creating an upload handler and download handler so that I can get the key of the uploaded blob and store it in my data model and use it later in the download handler?
I tried using the BlobInfo.all() to create a query the blobstore but I'm not able to get the key name field value of the entity.
This is my first interaction with the blobstore so I wouldn't mind advice on a better approach to the problem.
For serving a blob I would recommend you to look at the source code of the BlobstoreDownloadHandler. It should be easy to port it to bottle, since there's nothing very specific about the framework.
Here is an example on how to use BlobInfo.all():
for info in blobstore.BlobInfo.all():
self.response.out.write('Name:%s Key: %s Size:%s Creation:%s ContentType:%s<br>' % (info.filename, info.key(), info.size, info.creation, info.content_type))
for downloads you only really need to generate a response that includes the header "X-AppEngine-BlobKey:[your blob_key]" along with everything else you need like a Content-Disposition header if desired. or if it's an image you should probably just use the high performance image serving api, generate a url and redirect to it.... done
for uploads, besides writing a handler for appengine to call once the upload is safely in blobstore (that's in the docs)
You need a way to find the blob info in the incoming request. I have no idea what the request looks like in bottle. The Blobstoreuploadhandler has a get_uploads method and there's really no reason it needs to be an instance method as far as I can tell. So here's an example generic implementation of it that expects a webob request. For bottle you would need to write something similar that is compatible with bottles request object.
def get_uploads(request, field_name=None):
"""Get uploads for this request.
Args:
field_name: Only select uploads that were sent as a specific field.
populate_post: Add the non blob fields to request.POST
Returns:
A list of BlobInfo records corresponding to each upload.
Empty list if there are no blob-info records for field_name.
stolen from the SDK since they only provide a way to get to this
crap through their crappy webapp framework
"""
if not getattr(request, "__uploads", None):
request.__uploads = {}
for key, value in request.params.items():
if isinstance(value, cgi.FieldStorage):
if 'blob-key' in value.type_options:
request.__uploads.setdefault(key, []).append(
blobstore.parse_blob_info(value))
if field_name:
try:
return list(request.__uploads[field_name])
except KeyError:
return []
else:
results = []
for uploads in request.__uploads.itervalues():
results += uploads
return results
For anyone looking for this answer in future, to do this you need bottle (d'oh!) and defnull's multipart module.
Since creating upload URLs is generally simple enough and as per GAE docs, I'll just cover the upload handler.
from bottle import request
from multipart import parse_options_header
from google.appengine.ext.blobstore import BlobInfo
def get_blob_info(field_name):
try:
field = request.files[field_name]
except KeyError:
# Maybe form isn't multipart or file wasn't uploaded, or some such error
return None
blob_data = parse_options_header(field.content_type)[1]
try:
return BlobInfo.get(blob_data['blob-key'])
except KeyError:
# Malformed request? Wrong field name?
return None
Sorry if there are any errors in the code, it's off the top of my head.