sampler.py

import base64
import json
from handler import EndpointHandler
from PIL import Image
import io

# Initialize the handler
handler = EndpointHandler()

# Read a sample reference image and encode it in base64
with open("rithwik.png", "rb") as image_file:
    ref_image_base64 = base64.b64encode(image_file.read()).decode("utf-8")

# Define sample inputs
inputs = {
    "inputs": {
        "ref_image": ref_image_base64,
        "pose_video_path": "pose_video.mp4",
        "width": 512,
        "height": 768,
        "length": 12,
        "num_inference_steps": 25,
        "cfg": 3.5,
        "seed": 123
    }
}

# Simulate an inference call
output = handler(inputs)

# Decode the base64 video output
video_base64 = output.get("video", "")
video_bytes = base64.b64decode(video_base64)

# Save the video to a file
with open("output_video.mp4", "wb") as video_file:
    video_file.write(video_bytes)

print("Inference completed. Output video saved as output_video.mp4")