Images

Understand your images with the power of AI.

Via URL

To get predictions for an input, you need to supply an image and the model you'd like to get predictions from. You can supply an image either with a publicly accessible URL or by directly sending bytes. You can send up to 128 images in one API call. You specify the model you'd like to use with the {model-id} parameter.

Below is an example of how you would send image URLs and receive back predictions from the general model.

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiOutputResponse postModelOutputsResponse = stub.postModelOutputs(
    PostModelOutputsRequest.newBuilder()
        .setModelId("{THE_MODEL_ID}")
        .setVersionId("{THE_MODEL_VERSION_ID")  // This is optional. Defaults to the latest model version.
        .addInputs(
            Input.newBuilder().setData(
                Data.newBuilder().setImage(
                    Image.newBuilder().setUrl("https://samples.clarifai.com/metro-north.jpg")
                )
            )
        )
        .build()
);

if (postModelOutputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
  throw new RuntimeException("Post model outputs failed, status: " + postModelOutputsResponse.getStatus());
}

// Since we have one input, one output will exist here.
Output output = postModelOutputsResponse.getOutputs(0);

System.out.println("Predicted concepts:");
for (Concept concept : output.getData().getConceptsList()) {
    System.out.printf("%s %.2f%n", concept.getName(), concept.getValue());
}
{
  "status": {
    "code": 10000,
    "description": "Ok"
  },
  "outputs": [
    {
      "id": "ea68cac87c304b28a8046557062f34a0",
      "status": {
        "code": 10000,
        "description": "Ok"
      },
      "created_at": "2016-11-22T16:50:25Z",
      "model": {
        "name": "general-v1.3",
        "id": "aaa03c23b3724a16a56b629203edc62c",
        "created_at": "2016-03-09T17:11:39Z",
        "app_id": null,
        "output_info": {
          "message": "Show output_info with: GET /models/{model_id}/output_info",
          "type": "concept"
        },
        "model_version": {
          "id": "aa9ca48295b37401f8af92ad1af0d91d",
          "created_at": "2016-07-13T01:19:12Z",
          "status": {
            "code": 21100,
            "description": "Model trained successfully"
          }
        }
      },
      "input": {
        "id": "ea68cac87c304b28a8046557062f34a0",
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/metro-north.jpg"
          }
        }
      },
      "data": {
        "concepts": [
          {
            "id": "ai_HLmqFqBf",
            "name": "train",
            "app_id": null,
            "value": 0.9989112
          },
          {
            "id": "ai_fvlBqXZR",
            "name": "railway",
            "app_id": null,
            "value": 0.9975532
          },
          {
            "id": "ai_Xxjc3MhT",
            "name": "transportation system",
            "app_id": null,
            "value": 0.9959158
          },
          {
            "id": "ai_6kTjGfF6",
            "name": "station",
            "app_id": null,
            "value": 0.992573
          },
          {
            "id": "ai_RRXLczch",
            "name": "locomotive",
            "app_id": null,
            "value": 0.992556
          },
          {
            "id": "ai_VRmbGVWh",
            "name": "travel",
            "app_id": null,
            "value": 0.98789215
          },
          {
            "id": "ai_SHNDcmJ3",
            "name": "subway system",
            "app_id": null,
            "value": 0.9816359
          },
          {
            "id": "ai_jlb9q33b",
            "name": "commuter",
            "app_id": null,
            "value": 0.9712483
          },
          {
            "id": "ai_46lGZ4Gm",
            "name": "railroad track",
            "app_id": null,
            "value": 0.9690325
          },
          {
            "id": "ai_tr0MBp64",
            "name": "traffic",
            "app_id": null,
            "value": 0.9687052
          },
          {
            "id": "ai_l4WckcJN",
            "name": "blur",
            "app_id": null,
            "value": 0.9667078
          },
          {
            "id": "ai_2gkfMDsM",
            "name": "platform",
            "app_id": null,
            "value": 0.9624243
          },
          {
            "id": "ai_CpFBRWzD",
            "name": "urban",
            "app_id": null,
            "value": 0.960752
          },
          {
            "id": "ai_786Zr311",
            "name": "no person",
            "app_id": null,
            "value": 0.95864904
          },
          {
            "id": "ai_6lhccv44",
            "name": "business",
            "app_id": null,
            "value": 0.95720303
          },
          {
            "id": "ai_971KsJkn",
            "name": "track",
            "app_id": null,
            "value": 0.9494642
          },
          {
            "id": "ai_WBQfVV0p",
            "name": "city",
            "app_id": null,
            "value": 0.94089437
          },
          {
            "id": "ai_dSCKh8xv",
            "name": "fast",
            "app_id": null,
            "value": 0.9399334
          },
          {
            "id": "ai_TZ3C79C6",
            "name": "road",
            "app_id": null,
            "value": 0.93121606
          },
          {
            "id": "ai_VSVscs9k",
            "name": "terminal",
            "app_id": null,
            "value": 0.9230834
          }
        ]
      }
    }
  ]
}

Via bytes

Below is an example of how you would send the bytes of an image and receive back predictions from the general model.

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;
import com.google.protobuf.ByteString;
import java.io.File;
import java.nio.file.Files;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiOutputResponse postModelOutputsResponse = stub.postModelOutputs(
    PostModelOutputsRequest.newBuilder()
        .setModelId("{THE_MODEL_ID}")
        .setVersionId("{THE_MODEL_VERSION_ID")  // This is optional. Defaults to the latest model version.
        .addInputs(
            Input.newBuilder().setData(
                Data.newBuilder().setImage(
                    Image.newBuilder()
                        .setBase64(ByteString.copyFrom(Files.readAllBytes(
                            new File("{YOUR_IMAGE_FILE_LOCATION}").toPath()
                        )))
                )
            )
        )
        .build()
);

if (postModelOutputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
  throw new RuntimeException("Post model outputs failed, status: " + postModelOutputsResponse.getStatus());
}

// Since we have one input, one output will exist here.
Output output = postModelOutputsResponse.getOutputs(0);

System.out.println("Predicted concepts:");
for (Concept concept : output.getData().getConceptsList()) {
    System.out.printf("%s %.2f%n", concept.getName(), concept.getValue());
}
{
  "status": {
    "code": 10000,
    "description": "Ok"
  },
  "outputs": [
    {
      "id": "e1cf385843b94c6791bbd9f2654db5c0",
      "status": {
        "code": 10000,
        "description": "Ok"
      },
      "created_at": "2016-11-22T16:59:23Z",
      "model": {
        "name": "general-v1.3",
        "id": "aaa03c23b3724a16a56b629203edc62c",
        "created_at": "2016-03-09T17:11:39Z",
        "app_id": null,
        "output_info": {
          "message": "Show output_info with: GET /models/{model_id}/output_info",
          "type": "concept"
        },
        "model_version": {
          "id": "aa9ca48295b37401f8af92ad1af0d91d",
          "created_at": "2016-07-13T01:19:12Z",
          "status": {
            "code": 21100,
            "description": "Model trained successfully"
          }
        }
      },
      "input": {
        "id": "e1cf385843b94c6791bbd9f2654db5c0",
        "data": {
          "image": {
            "url": "https://s3.amazonaws.com/clarifai-api/img/prod/b749af061d564b829fb816215f6dc832/e11c81745d6d42a78ef712236023df1c.jpeg"
          }
        }
      },
      "data": {
        "concepts": [
          {
            "id": "ai_l4WckcJN",
            "name": "blur",
            "app_id": null,
            "value": 0.9973569
          },
          {
            "id": "ai_786Zr311",
            "name": "no person",
            "app_id": null,
            "value": 0.98865616
          },
          {
            "id": "ai_JBPqff8z",
            "name": "art",
            "app_id": null,
            "value": 0.986006
          },
          {
            "id": "ai_5rD7vW4j",
            "name": "wallpaper",
            "app_id": null,
            "value": 0.9722556
          },
          {
            "id": "ai_sTjX6dqC",
            "name": "abstract",
            "app_id": null,
            "value": 0.96476805
          },
          {
            "id": "ai_Dm5GLXnB",
            "name": "illustration",
            "app_id": null,
            "value": 0.922542
          },
          {
            "id": "ai_5xjvC0Tj",
            "name": "background",
            "app_id": null,
            "value": 0.8775655
          },
          {
            "id": "ai_tBcWlsCp",
            "name": "nature",
            "app_id": null,
            "value": 0.87474406
          },
          {
            "id": "ai_rJGvwlP0",
            "name": "insubstantial",
            "app_id": null,
            "value": 0.8196385
          },
          {
            "id": "ai_2Bh4VMrb",
            "name": "artistic",
            "app_id": null,
            "value": 0.8142488
          },
          {
            "id": "ai_mKzmkKDG",
            "name": "Christmas",
            "app_id": null,
            "value": 0.7996079
          },
          {
            "id": "ai_RQccV41p",
            "name": "woman",
            "app_id": null,
            "value": 0.7955615
          },
          {
            "id": "ai_20SCBBZ0",
            "name": "vector",
            "app_id": null,
            "value": 0.7775099
          },
          {
            "id": "ai_4sJLn6nX",
            "name": "dark",
            "app_id": null,
            "value": 0.7715479
          },
          {
            "id": "ai_5Kp5FMJw",
            "name": "still life",
            "app_id": null,
            "value": 0.7657637
          },
          {
            "id": "ai_LM64MDHs",
            "name": "shining",
            "app_id": null,
            "value": 0.7542407
          },
          {
            "id": "ai_swtdphX8",
            "name": "love",
            "app_id": null,
            "value": 0.74926054
          },
          {
            "id": "ai_h45ZTxZl",
            "name": "square",
            "app_id": null,
            "value": 0.7449074
          },
          {
            "id": "ai_cMfj16kJ",
            "name": "design",
            "app_id": null,
            "value": 0.73926914
          },
          {
            "id": "ai_LxrzLJmf",
            "name": "bright",
            "app_id": null,
            "value": 0.73790145
          }
        ]
      }
    }
  ]
}

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