Video
Make predictions on video inputs
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Make predictions on video inputs
Last updated
Was this helpful?
With a video input, the Predict API response will return a list of predicted concepts for every frame of a video. By default, video is processed at 1 frame per second (but this is configurable in the predict request). This means you will receive a list of concepts for every second of your video.
You can run Predict on your video using a select number of . The models that are currently supported are: Apparel, Food, General, NSFW, Travel, and Wedding. You make an API call by providing the {model-id} parameter and your data parameter is video instead of image.
Video limits
The Predict API has limits to the length and size it can support. A video, uploaded through URL, can be anywhere up to 80MB in size or 10mins in length. When a video is sent through by bytes, the Predict API can support 10MB in size.
If your video exceeds the limits, please follow our on how to break up a large video into smaller components, and send those into the Video API. Otherwise, the processing will time out and you will receive an error response.
Via URL
Below is an example of how you would send video 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().setVideo(
Video.newBuilder().setUrl("https://samples.clarifai.com/beer.mp4")
)
)
)
.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);
// A separate prediction is available for each "frame".
for (Frame frame : output.getData().getFramesList()) {
System.out.println("Predicted concepts on frame " + frame.getFrameInfo().getTime() + ":");
for (Concept concept : frame.getData().getConceptsList()) {
System.out.printf("\t%s %.2f%n", concept.getName(), concept.getValue());
}
}// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions
stub.PostModelOutputs(
{
model_id: "{THE_MODEL_ID}",
version_id: "{THE_MODEL_VERSION_ID}", // This is optional. Defaults to the latest model version.
inputs: [
{data: {video: {url: "https://samples.clarifai.com/beer.mp4"}}}
]
},
metadata,
(err, response) => {
if (err) {
throw new Error(err);
}
if (response.status.code !== 10000) {
throw new Error("Post model outputs failed, status: " + response.status.description);
}
// Since we have one input, one output will exist here.
const output = response.outputs[0]
// A separate prediction is available for each "frame".
for (const frame of output.data.frames) {
console.log("Predicted concepts on frame " + frame.frame_info.time + ":");
for (const concept of frame.data.concepts) {
console.log("\t" + concept.name + " " + concept.value);
}
}
}
);# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions
post_model_outputs_response = stub.PostModelOutputs(
service_pb2.PostModelOutputsRequest(
model_id="{THE_MODEL_ID}",
version_id="{THE_MODEL_VERSION_ID}", # This is optional. Defaults to the latest model version.
inputs=[
resources_pb2.Input(
data=resources_pb2.Data(
video=resources_pb2.Video(
url="https://samples.clarifai.com/beer.mp4"
)
)
)
]
),
metadata=metadata
)
if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
raise Exception("Post model outputs failed, status: " + post_model_outputs_response.status.description)
# Since we have one input, one output will exist here.
output = post_model_outputs_response.outputs[0]
# A separate prediction is available for each "frame".
for frame in output.data.frames:
print("Predicted concepts on frame " + str(frame.frame_info.time) + ":")
for concept in frame.data.concepts:
print("\t%s %.2f" % (concept.name, concept.value))curl -X POST \
-H "Authorization: Key YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '
{
"inputs": [
{
"data": {
"video": {
"url": "https://samples.clarifai.com/beer.mp4"
}
}
}
]
}'\
https://api.clarifai.com/v2/models/{THE_MODEL_ID}/versions/{THE_MODEL_VERSION_ID}/outputs
# Model version ID is optional. It defaults to the latest model version.{
"status": {
"code": 10000,
"description": "Ok"
},
"outputs": [
{
"id": "d8234da5d1f04ca8a2e13e34d51f9b85",
"status": {
"code": 10000,
"description": "Ok"
},
"created_at": "2017-06-28T14:58:41.835370141Z",
"model": {
"id": "aaa03c23b3724a16a56b629203edc62c",
"name": "general-v1.3",
"created_at": "2016-03-09T17:11:39.608845Z",
"app_id": "main",
"output_info": {
"message": "Show output_info with: GET /models/{model_id}/output_info",
"type": "concept",
"type_ext": "concept"
},
"model_version": {
"id": "aa9ca48295b37401f8af92ad1af0d91d",
"created_at": "2016-07-13T01:19:12.147644Z",
"status": {
"code": 21100,
"description": "Model trained successfully"
}
}
},
"input": {
"id": "f0fc1a005f124d389da4d80823a3125b",
"data": {
"video": {
"url": "https://samples.clarifai.com/beer.mp4"
}
}
},
"data": {
"frames": [
{
"frame_info": {
"index": 0,
"time": 0
},
"data": {
"concepts": [
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.98658466,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.97975093,
"app_id": "main"
},
{
"id": "ai_drK6ClJR",
"name": "alcohol",
"value": 0.9783862,
"app_id": "main"
},
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.97157896,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.969543,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.96628696,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.95581007,
"app_id": "main"
},
{
"id": "ai_Lq00FggW",
"name": "desktop",
"value": 0.92861253,
"app_id": "main"
},
{
"id": "ai_7vR9zv7l",
"name": "bubble",
"value": 0.9082134,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9020835,
"app_id": "main"
},
{
"id": "ai_7Xg5SQRW",
"name": "luxury",
"value": 0.8990605,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.89708906,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.8938055,
"app_id": "main"
},
{
"id": "ai_7qwGxLch",
"name": "gold",
"value": 0.8892093,
"app_id": "main"
},
{
"id": "ai_wmbvr5TG",
"name": "celebration",
"value": 0.88606626,
"app_id": "main"
},
{
"id": "ai_4lvjn8qv",
"name": "closeup",
"value": 0.881963,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.8674431,
"app_id": "main"
},
{
"id": "ai_12dz73B9",
"name": "bottle",
"value": 0.86288416,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.86252767,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.86069393,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 1,
"time": 1000
},
"data": {
"concepts": [
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.98658466,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.97975093,
"app_id": "main"
},
{
"id": "ai_drK6ClJR",
"name": "alcohol",
"value": 0.9783862,
"app_id": "main"
},
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.97157896,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.969543,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.96628696,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.95581007,
"app_id": "main"
},
{
"id": "ai_7vR9zv7l",
"name": "bubble",
"value": 0.9082134,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9020835,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.89708906,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.8938055,
"app_id": "main"
},
{
"id": "ai_7qwGxLch",
"name": "gold",
"value": 0.8834515,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.8674431,
"app_id": "main"
},
{
"id": "ai_b01mhdxB",
"name": "party",
"value": 0.8603341,
"app_id": "main"
},
{
"id": "ai_XNmzgDnF",
"name": "pub",
"value": 0.85809004,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.85319245,
"app_id": "main"
},
{
"id": "ai_Lq00FggW",
"name": "desktop",
"value": 0.8506696,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.84634554,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.8446485,
"app_id": "main"
},
{
"id": "ai_wmbvr5TG",
"name": "celebration",
"value": 0.8383831,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 2,
"time": 2000
},
"data": {
"concepts": [
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.9856042,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.97975093,
"app_id": "main"
},
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.9755833,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.9733174,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.969543,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.94170487,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.92778283,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.9227257,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9179274,
"app_id": "main"
},
{
"id": "ai_drK6ClJR",
"name": "alcohol",
"value": 0.90887475,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9045203,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.8938055,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.87420183,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.8699659,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.8674431,
"app_id": "main"
},
{
"id": "ai_XNmzgDnF",
"name": "pub",
"value": 0.85809004,
"app_id": "main"
},
{
"id": "ai_Lq00FggW",
"name": "desktop",
"value": 0.8506696,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.8446485,
"app_id": "main"
},
{
"id": "ai_qNxqNBWN",
"name": "cream",
"value": 0.844169,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.8397074,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 3,
"time": 3000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.996614,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.9794438,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.9733174,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.9645849,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.94761443,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.92864025,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.9227257,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.91797745,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9179274,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.904904,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9045203,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.889248,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.8689867,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.86591685,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.8546975,
"app_id": "main"
},
{
"id": "ai_mZ2tl6cW",
"name": "health",
"value": 0.8544879,
"app_id": "main"
},
{
"id": "ai_cHsR7RS8",
"name": "milk",
"value": 0.852397,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.8446485,
"app_id": "main"
},
{
"id": "ai_qNxqNBWN",
"name": "cream",
"value": 0.844169,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.837438,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 4,
"time": 4000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.996614,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.9748836,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.9645849,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.96217895,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9179274,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.904904,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9045203,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.9030821,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.8983356,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.894987,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.894392,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.889248,
"app_id": "main"
},
{
"id": "ai_mZ2tl6cW",
"name": "health",
"value": 0.8860091,
"app_id": "main"
},
{
"id": "ai_4sJLn6nX",
"name": "dark",
"value": 0.8837219,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.8712319,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.8695712,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.8664293,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.8546975,
"app_id": "main"
},
{
"id": "ai_cHsR7RS8",
"name": "milk",
"value": 0.852397,
"app_id": "main"
},
{
"id": "ai_qNxqNBWN",
"name": "cream",
"value": 0.844169,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 5,
"time": 5000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.997158,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.97719705,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.9748836,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.96217895,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.9210669,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9124408,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.90667903,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.904904,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9046865,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.9030821,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.90262496,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.8983356,
"app_id": "main"
},
{
"id": "ai_4sJLn6nX",
"name": "dark",
"value": 0.8947689,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.894392,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.8852426,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.8789175,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.8762902,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.87279737,
"app_id": "main"
},
{
"id": "ai_mZ2tl6cW",
"name": "health",
"value": 0.8544879,
"app_id": "main"
},
{
"id": "ai_cHsR7RS8",
"name": "milk",
"value": 0.849733,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 6,
"time": 6000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.99790645,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.97817445,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.97463626,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.9659773,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.9273318,
"app_id": "main"
},
{
"id": "ai_4sJLn6nX",
"name": "dark",
"value": 0.9219268,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9185593,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.91295856,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9119204,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.91089505,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.9056676,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.90262496,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.89882934,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.8932399,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.892028,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.88797945,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.88745904,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.87949455,
"app_id": "main"
},
{
"id": "ai_MmRdqDFp",
"name": "soap",
"value": 0.87376094,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.8715329,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 7,
"time": 7000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.99790645,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.97817445,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.97463626,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.9659773,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.9273318,
"app_id": "main"
},
{
"id": "ai_4sJLn6nX",
"name": "dark",
"value": 0.9219268,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9185593,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.91295856,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9119204,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.91089505,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.9056676,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.90262496,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.89882934,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.8932399,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.892028,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.8913312,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.88745904,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.87949455,
"app_id": "main"
},
{
"id": "ai_MmRdqDFp",
"name": "soap",
"value": 0.87376094,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.8715329,
"app_id": "main"
}
]
}
},
{
"frame_info": {
"index": 8,
"time": 8000
},
"data": {
"concepts": [
{
"id": "ai_8XGJjH7R",
"name": "foam",
"value": 0.99790645,
"app_id": "main"
},
{
"id": "ai_TBlp0Pt3",
"name": "beer",
"value": 0.97817445,
"app_id": "main"
},
{
"id": "ai_786Zr311",
"name": "no person",
"value": 0.97463626,
"app_id": "main"
},
{
"id": "ai_zJx6RbxW",
"name": "drink",
"value": 0.9659773,
"app_id": "main"
},
{
"id": "ai_4sJLn6nX",
"name": "dark",
"value": 0.9219268,
"app_id": "main"
},
{
"id": "ai_pkvDRSJ1",
"name": "mug",
"value": 0.9210669,
"app_id": "main"
},
{
"id": "ai_B3MXt5Ng",
"name": "refreshment",
"value": 0.9185593,
"app_id": "main"
},
{
"id": "ai_2gmKZLxp",
"name": "cold",
"value": 0.91295856,
"app_id": "main"
},
{
"id": "ai_3PlgVmlN",
"name": "food",
"value": 0.9119204,
"app_id": "main"
},
{
"id": "ai_54zxXFGL",
"name": "full",
"value": 0.91089505,
"app_id": "main"
},
{
"id": "ai_SsmKLB4z",
"name": "bar",
"value": 0.9056676,
"app_id": "main"
},
{
"id": "ai_BrnHNkt0",
"name": "coffee",
"value": 0.90262496,
"app_id": "main"
},
{
"id": "ai_mCpQg89c",
"name": "glass",
"value": 0.89882934,
"app_id": "main"
},
{
"id": "ai_7D0mdp1W",
"name": "delicious",
"value": 0.894392,
"app_id": "main"
},
{
"id": "ai_WbwL0pPL",
"name": "breakfast",
"value": 0.8932399,
"app_id": "main"
},
{
"id": "ai_zFnPQdgB",
"name": "wood",
"value": 0.88797945,
"app_id": "main"
},
{
"id": "ai_3R5pJ6hB",
"name": "lager",
"value": 0.88745904,
"app_id": "main"
},
{
"id": "ai_8LWlDfFD",
"name": "table",
"value": 0.87949455,
"app_id": "main"
},
{
"id": "ai_MmRdqDFp",
"name": "soap",
"value": 0.87376094,
"app_id": "main"
},
{
"id": "ai_5VHsZr8N",
"name": "liquid",
"value": 0.8715329,
"app_id": "main"
}
]
}
}
]
}
}
]
}Via bytes
Below is an example of how you would send the bytes of a video 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().setVideo(
Video.newBuilder()
.setBase64(ByteString.copyFrom(Files.readAllBytes(
new File("{YOUR_VIDEO_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);
// A separate prediction is available for each "frame".
for (Frame frame : output.getData().getFramesList()) {
System.out.println("Predicted concepts on frame " + frame.getFrameInfo().getTime() + ":");
for (Concept concept : frame.getData().getConceptsList()) {
System.out.printf("\t%s %.2f%n", concept.getName(), concept.getValue());
}
}// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions
const fs = require("fs");
const videoBytes = fs.readFileSync("{YOUR_VIDEO_FILE_LOCATION}");
stub.PostModelOutputs(
{
model_id: "{THE_MODEL_ID}",
version_id: "{YOUR_MODEL_VERSION_ID}", // This is optional. Defaults to the latest model version.
inputs: [
{data: {video: {base64: videoBytes}}}
]
},
metadata,
(err, response) => {
if (err) {
throw new Error(err);
}
if (response.status.code !== 10000) {
throw new Error("Post model outputs failed, status: " + response.status.description);
}
// Since we have one input, one output will exist here.
const output = response.outputs[0]
// A separate prediction is available for each "frame".
for (const frame of output.data.frames) {
console.log("Predicted concepts on frame " + frame.frame_info.time + ":");
for (const concept of frame.data.concepts) {
console.log("\t" + concept.name + " " + concept.value);
}
}
}
);# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions
with open("{YOUR_VIDEO_FILE_LOCATION}", "rb") as f:
file_bytes = f.read()
post_model_outputs_response = stub.PostModelOutputs(
service_pb2.PostModelOutputsRequest(
model_id="{THE_MODEL_ID}",
version_id="{THE_MODEL_VERSION_ID}", # This is optional. Defaults to the latest model version.
inputs=[
resources_pb2.Input(
data=resources_pb2.Data(
video=resources_pb2.Video(
base64=file_bytes
)
)
)
]
),
metadata=metadata
)
if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
raise Exception("Post model outputs failed, status: " + post_model_outputs_response.status.description)
# Since we have one input, one output will exist here.
output = post_model_outputs_response.outputs[0]
# A separate prediction is available for each "frame".
for frame in output.data.frames:
print("Predicted concepts on frame " + str(frame.frame_info.time) + ":")
for concept in frame.data.concepts:
print("\t%s %.2f" % (concept.name, concept.value))curl -X POST \
-H "Authorization: Key YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '
{
"inputs": [
{
"data": {
"video": {
"base64": "'"$(base64 video_file_path.mp4)"'"
}
}
}
]
}'\
https://api.clarifai.com/v2/models/{THE_MODEL_ID}/versions/{THE_MODEL_VERSION_ID}/outputs
# The model version ID is optional. It defaults to the latest model version.{
"status": {
"code": 10000,
"description": "Ok"
},
"outputs": [
{
"id": "f6f9e1b007d742fb9d777f35cf3bffd0",
"status": {
"code": 10000,
"description": "Ok"
},
"created_at": "2017-06-28T16:00:51.258194418Z",
"model": {
"id": "aaa03c23b3724a16a56b629203edc62c",
"name": "general-v1.3",
"created_at": "2016-03-09T17:11:39.608845Z",
"app_id": "main",
"output_info": {
"message": "Show output_info with: GET /models/{model_id}/output_info",
"type": "concept",
"type_ext": "concept"
},
"model_version": {
"id": "aa9ca48295b37401f8af92ad1af0d91d",
"created_at": "2016-07-13T01:19:12.147644Z",
"status": {
"code": 21100,
"description": "Model trained successfully"
}
}
},
"input": {
"id": "b17d29ad1b714869a8c729e510ab22d0",
"data": {
"video": {
"url": "https://s3.amazonaws.com/clarifai-api/vid/prod/ib81c84d5b2341858b86da18a2bd21d2/e86fbf516521425098081dd42e157a12",
"base64": "true"
}
}
},
"data": {
"frames": [
{
"frame_info": {
"index": 0,
"time": 0
},
"data": {
"concepts": [
{
"id": "ai_VTlCx2f2",
"name": "window",
"value": 0.99909437,
"app_id": "main"
},
{
"id": "ai_l8TKp2h5",
"name": "people",
"value": 0.99610686,
"app_id": "main"
},
{
"id": "ai_VPmHr5bm",
"name": "adult",
"value": 0.9958472,
"app_id": "main"
},
{
"id": "ai_SVshtN54",
"name": "one",
"value": 0.9937376,
"app_id": "main"
},
{
"id": "ai_TJ9wFfK5",
"name": "portrait",
"value": 0.9899301,
"app_id": "main"
},
{
"id": "ai_ZrPNDjxN",
"name": "daylight",
"value": 0.9885398,
"app_id": "main"
},
{
"id": "ai_dxSG2s86",
"name": "man",
"value": 0.9833108,
"app_id": "main"
},
{
"id": "ai_86sS08Pw",
"name": "wear",
"value": 0.9807093,
"app_id": "main"
},
{
"id": "ai_GxSDhQ34",
"name": "facial expression",
"value": 0.9769263,
"app_id": "main"
},
{
"id": "ai_Pf2b7clG",
"name": "indoors",
"value": 0.96838474,
"app_id": "main"
},
{
"id": "ai_VRmbGVWh",
"name": "travel",
"value": 0.96641624,
"app_id": "main"
},
{
"id": "ai_XNzGRk0F",
"name": "side view",
"value": 0.9603646,
"app_id": "main"
},
{
"id": "ai_Zmhsv0Ch",
"name": "outdoors",
"value": 0.9434113,
"app_id": "main"
},
{
"id": "ai_n9vjC1jB",
"name": "light",
"value": 0.94182396,
"app_id": "main"
},
{
"id": "ai_WcnFrjw1",
"name": "backlit",
"value": 0.9347838,
"app_id": "main"
},
{
"id": "ai_QKqjh1CM",
"name": "vehicle window",
"value": 0.92699903,
"app_id": "main"
},
{
"id": "ai_mlrv94tv",
"name": "reflection",
"value": 0.90993655,
"app_id": "main"
},
{
"id": "ai_41s912fX",
"name": "fair weather",
"value": 0.90100014,
"app_id": "main"
},
{
"id": "ai_rsX6XWc2",
"name": "building",
"value": 0.88111985,
"app_id": "main"
},
{
"id": "ai_L83krFdq",
"name": "veil",
"value": 0.8785704,
"app_id": "main"
}
]
}
}
]
}
}
]
}