CLIPImageClassifier wraps clip image model from transformers

Overview

CLIPImageClassifier

CLIPImageClassifier wraps clip image model from transformers.

CLIPImageClassifier is initialized with the argument classes, these are the texts that we want to classify an image to one of them The executor receives Documents with uri attribute. Each Document's uri represent the path to an image. The executor will read the image and classify it to one of the classes.

The result will be saved inside a new tag called class within the original document. The class tag is a dictionary that contains two things:

  • label: the chosen class from classes.
  • score: the confidence score in the chosen class given by the model.

Usage

Use the prebuilt images from Jina Hub in your Python code, add it to your Flow and classify your images according to chosen classes:

from jina import Flow
classes = ['this is a cat','this is a dog','this is a person']
f = Flow().add(
    uses='jinahub+docker://CLIPImageClassifier',
    uses_with={'classes':classes}
    )
docs = DocumentArray()
doc = Document(uri='/your/image/path')
docs.append(doc)

with f:
    f.post(on='/classify', inputs=docs, on_done=lambda resp: print(resp.docs[0].tags['class']['label']))

Returns

Document with class tag. This class tag which is a dict.It contains label which is an str and a float confidence score for the image.

GPU Usage

This executor also offers a GPU version. To use it, make sure to pass 'device'='cuda', as the initialization parameter, and gpus='all' when adding the containerized Executor to the Flow. See the Executor on GPU section of Jina documentation for more details.

Here's how you would modify the example above to use a GPU:

from jina import Flow

classes = ['this is a cat','this is a dog','this is a person']	
f = Flow().add(
    uses='jinahub+docker://CLIPImageClassifier',
    uses_with={
    'classes':classes,
    'device':'cuda',
    'gpus':'all'
    }
    )
docs = DocumentArray()
doc = Document(uri='/your/image/path')
docs.append(doc)

with f:
    f.post(on='/classify', inputs=docs, on_done=lambda resp: print(resp.docs[0].tags['class']['label']))

Reference

CLIP Image model

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Comments
  • CLIPImageClassifier error

    CLIPImageClassifier error

    I tried to run the following flow on "jinahub+sandbox" but I got the following error could you please share your insight with me? I am running the code from my Jupyter notebook.

    import warnings warnings.filterwarnings("ignore", category=DeprecationWarning) from jina import Flow classes = ['this is a cat','this is a dog','this is a person'] doc = Document(uri='image/dog.jpg') docs = DocumentArray() docs.append(doc) f = Flow().add( uses='jinahub://CLIPImageClassifier',name="classifier", uses_with={'classes':classes})

    with f: f.post(on='/classify', inputs=docs, on_done=lambda resp: print(resp.docs[0].tags['class']['label']))

    -----------------------error------------------ PkgResourcesDeprecationWarning: 1.1build1 is an invalid version and will not be supported in a future release (raised from /home/ubuntu/pyenv/lib/python3.10/site-packages/pkg_resources/init.py:116) PkgResourcesDeprecationWarning: 0.1.43ubuntu1 is an invalid version and will not be supported in a future release (raised from /home/ubuntu/pyenv/lib/python3.10/site-packages/pkg_resources/init.py:116) UserWarning: VersionConflict(torchvision 0.12.0+cpu (/usr/local/lib/python3.10/dist-packages), Requirement.parse('torchvision==0.10.0')) (raised from /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/hubble/helper.py:483) ftfy or spacy is not installed using BERT BasicTokenizer instead of ftfy. ╭────── 🎉 Flow is ready to serve! ──────╮ │ 🔗 Protocol GRPC │ │ 🏠 Local 0.0.0.0:55600 │ │ 🔒 Private 172.31.17.247:55600 │ │ 🌍 Public 34.221.179.218:55600 │ ╰────────────────────────────────────────╯ ERROR classifier/rep-0@21134 AttributeError("'DocumentArrayInMemory' [07/06/22 16:34:35] object has no attribute 'get_attributes'")
    add "--quiet-error" to suppress the exception details
    ╭────────────── Traceback (most recent call last) ───────────────╮
    │ /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/serve/ru… │
    │ in process_data │
    │ │
    │ 162 │ │ │ │ if self.logger.debug_enabled: │
    │ 163 │ │ │ │ │ self._log_data_request(requests[0]) │
    │ 164 │ │ │ │ │
    │ ❱ 165 │ │ │ │ return await self._data_request_handler. │
    │ 166 │ │ │ except (RuntimeError, Exception) as ex: │
    │ 167 │ │ │ │ self.logger.error( │
    │ 168 │ │ │ │ │ f'{ex!r}' │
    │ │
    │ /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/serve/ru… │
    │ in handle │
    │ │
    │ 147 │ │ ) │
    │ 148 │ │ │
    │ 149 │ │ # executor logic │
    │ ❱ 150 │ │ return_data = await self._executor.acall( │
    │ 151 │ │ │ req_endpoint=requests[0].header.exec_endpoin │
    │ 152 │ │ │ docs=docs, │
    │ 153 │ │ │ parameters=params, │
    │ │
    │ /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/serve/ex… │
    │ in acall
    │ │
    │ 271 │ │ if req_endpoint in self.requests: │
    │ 272 │ │ │ return await self.acall_endpoint(req_end │
    │ 273 │ │ elif default_endpoint in self.requests: │
    │ ❱ 274 │ │ │ return await self.acall_endpoint(__defau │
    │ 275 │ │
    │ 276 │ async def acall_endpoint(self, req_endpoint, **k │
    │ 277 │ │ func = self.requests[req_endpoint] │
    │ │
    │ /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/serve/ex… │
    │ in acall_endpoint
    │ │
    │ 292 │ │ │ if iscoroutinefunction(func): │
    │ 293 │ │ │ │ return await func(self, **kwargs) │
    │ 294 │ │ │ else: │
    │ ❱ 295 │ │ │ │ return func(self, **kwargs) │
    │ 296 │ │
    │ 297 │ @property │
    │ 298 │ def workspace(self) -> Optional[str]: │
    │ │
    │ /home/ubuntu/pyenv/lib/python3.10/site-packages/jina/serve/ex… │
    │ in arg_wrapper │
    │ │
    │ 177 │ │ │ │ def arg_wrapper( │
    │ 178 │ │ │ │ │ executor_instance, *args, **kwargs │
    │ 179 │ │ │ │ ): # we need to get the summary from th │
    │ the self │
    │ ❱ 180 │ │ │ │ │ return fn(executor_instance, *args, │
    │ 181 │ │ │ │ │
    │ 182 │ │ │ │ self.fn = arg_wrapper │
    │ 183 │
    │ │
    │ /home/ubuntu/.jina/hub-package/9k3zudzu/clip_image_classifier… │
    │ in classify │
    │ │
    │ 56 │ │ for docs_batch in docs.traverse_flat( │
    │ 57 │ │ │ parameters.get('traversal_paths', self.traver │
    │ 58 │ │ ).batch(batch_size=parameters.get('batch_size', s │
    │ ❱ 59 │ │ │ image_batch = docs_batch.get_attributes('blob │
    │ 60 │ │ │ with torch.inference_mode(): │
    │ 61 │ │ │ │ input = self._generate_input_features(cla │
    │ 62 │ │ │ │ outputs = self.model(**input) │
    ╰────────────────────────────────────────────────────────────────╯
    AttributeError: 'DocumentArrayInMemory' object has no attribute
    'get_attributes'
    Exception in thread Thread-107: Traceback (most recent call last): File "/home/ubuntu/pyenv/lib/python3.10/site-packages/jina/clients/base/grpc.py", line 86, in _get_results async for resp in stub.Call( File "/home/ubuntu/pyenv/lib/python3.10/site-packages/grpc/aio/_call.py", line 326, in _fetch_stream_responses await self._raise_for_status() File "/home/ubuntu/pyenv/lib/python3.10/site-packages/grpc/aio/_call.py", line 236, in _raise_for_status raise _create_rpc_error(await self.initial_metadata(), await grpc.aio._call.AioRpcError: <AioRpcError of RPC that terminated with: status = StatusCode.UNKNOWN details = "Unexpected <class 'grpc.aio._call.AioRpcError'>: <AioRpcError of RPC that terminated with: status = StatusCode.UNKNOWN details = "Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'" debug_error_string = "{"created":"@1657125275.618452649","description":"Error received from peer ipv4:0.0.0.0:58903","file":"src/core/lib/surface/call.cc","file_line":952,"grpc_message":"Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'","grpc_status":2}"

    " debug_error_string = "{"created":"@1657125275.619606817","description":"Error received from peer ipv4:0.0.0.0:55600","file":"src/core/lib/surface/call.cc","file_line":952,"grpc_message":"Unexpected <class 'grpc.aio._call.AioRpcError'>: <AioRpcError of RPC that terminated with:\n\tstatus = StatusCode.UNKNOWN\n\tdetails = "Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'"\n\tdebug_error_string = "{"created":"@1657125275.618452649","description":"Error received from peer ipv4:0.0.0.0:58903","file":"src/core/lib/surface/call.cc","file_line":952,"grpc_message":"Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'","grpc_status":2}"\n>","grpc_status":2}"

    The above exception was the direct cause of the following exception:

    Traceback (most recent call last): File "/usr/lib/python3.10/threading.py", line 1009, in _bootstrap_inner self.run() File "/home/ubuntu/pyenv/lib/python3.10/site-packages/jina/helper.py", line 1292, in run self.result = asyncio.run(func(*args, **kwargs)) File "/usr/lib/python3.10/asyncio/runners.py", line 44, in run return loop.run_until_complete(main) File "/usr/lib/python3.10/asyncio/base_events.py", line 646, in run_until_complete return future.result() File "/home/ubuntu/pyenv/lib/python3.10/site-packages/jina/clients/mixin.py", line 164, in _get_results async for resp in c._get_results(*args, **kwargs): File "/home/ubuntu/pyenv/lib/python3.10/site-packages/jina/clients/base/grpc.py", line 155, in _get_results raise e File "/home/ubuntu/pyenv/lib/python3.10/site-packages/jina/clients/base/grpc.py", line 135, in _get_results raise BadClient(msg) from err jina.excepts.BadClient: gRPC error: StatusCode.UNKNOWN Unexpected <class 'grpc.aio._call.AioRpcError'>: <AioRpcError of RPC that terminated with: status = StatusCode.UNKNOWN details = "Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'" debug_error_string = "{"created":"@1657125275.618452649","description":"Error received from peer ipv4:0.0.0.0:58903","file":"src/core/lib/surface/call.cc","file_line":952,"grpc_message":"Unexpected <class 'TypeError'>: format_exception() got an unexpected keyword argument 'etype'","grpc_status":2}"


    AttributeError Traceback (most recent call last) File ~/pyenv/lib/python3.10/site-packages/jina/helper.py:1307, in run_async(func, *args, **kwargs) 1306 try: -> 1307 return thread.result 1308 except AttributeError:

    AttributeError: '_RunThread' object has no attribute 'result'

    During handling of the above exception, another exception occurred:

    BadClient Traceback (most recent call last) Input In [15], in <cell line: 12>() 8 f = Flow().add( 9 uses='jinahub://CLIPImageClassifier',name="classifier", 10 uses_with={'classes':classes}) 12 with f: ---> 13 f.post(on='/classify', inputs=docs, on_done=lambda resp: print(resp.docs[0].tags['class']['label']))

    File ~/pyenv/lib/python3.10/site-packages/jina/clients/mixin.py:173, in PostMixin.post(self, on, inputs, on_done, on_error, on_always, parameters, target_executor, request_size, show_progress, continue_on_error, return_responses, **kwargs) 170 if return_results: 171 return result --> 173 return run_async( 174 _get_results, 175 inputs=inputs, 176 on_done=on_done, 177 on_error=on_error, 178 on_always=on_always, 179 exec_endpoint=on, 180 target_executor=target_executor, 181 parameters=parameters, 182 request_size=request_size, 183 **kwargs, 184 )

    File ~/pyenv/lib/python3.10/site-packages/jina/helper.py:1311, in run_async(func, *args, **kwargs) 1308 except AttributeError: 1309 from jina.excepts import BadClient -> 1311 raise BadClient( 1312 'something wrong when running the eventloop, result can not be retrieved' 1313 ) 1314 else: 1316 raise RuntimeError( 1317 'you have an eventloop running but not using Jupyter/ipython, ' 1318 'this may mean you are using Jina with other integration? if so, then you ' 1319 'may want to use Client/Flow(asyncio=True). If not, then ' 1320 'please report this issue here: https://github.com/jina-ai/jina' 1321 )

    BadClient: something wrong when running the eventloop, result can not be retrieved

    opened by sk-haghighi 4
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