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import os |
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import streamlit as st |
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from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel |
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from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc |
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from clarifai_grpc.grpc.api.status import status_code_pb2 |
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import io |
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def get_image_concepts(image_bytes): |
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channel = ClarifaiChannel.get_grpc_channel() |
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stub = service_pb2_grpc.V2Stub(channel) |
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PAT = os.getenv('CLARIFAI_PAT') |
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USER_ID = 'clarifai' |
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APP_ID = 'main' |
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MODEL_ID = 'general-image-detection' |
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MODEL_VERSION_ID = '1580bb1932594c93b7e2e04456af7c6f' |
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metadata = (('authorization', 'Key ' + PAT),) |
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userDataObject = resources_pb2.UserAppIDSet(user_id=USER_ID, app_id=APP_ID) |
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post_model_outputs_response = stub.PostModelOutputs( |
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service_pb2.PostModelOutputsRequest( |
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user_app_id=userDataObject, |
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model_id=MODEL_ID, |
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version_id=MODEL_VERSION_ID, |
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inputs=[ |
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resources_pb2.Input( |
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data=resources_pb2.Data( |
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image=resources_pb2.Image( |
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base64=image_bytes |
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) |
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) |
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) |
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] |
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), |
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metadata=metadata |
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) |
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if post_model_outputs_response.status.code != status_code_pb2.SUCCESS: |
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raise Exception("Post model outputs failed, status: " + post_model_outputs_response.status.description) |
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return post_model_outputs_response.outputs[0].data.regions |
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st.title("Image Detection with Clarifai") |
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uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) |
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if uploaded_file is not None: |
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image_bytes = uploaded_file.getvalue() |
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regions = get_image_concepts(image_bytes) |
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for region in regions: |
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for concept in region.data.concepts: |
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name = concept.name |
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value = round(concept.value, 4) |
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st.write(f"{name}: {value}") |
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