| import base64 |
| import glob |
| from openai import OpenAI |
| import cv2 |
|
|
| BASE_URL = "http://localhost:8000/v1" |
|
|
| def img_to_data_url(img_path: str): |
| img = cv2.imread(img_path) |
| if img is None: |
| raise FileNotFoundError(f"Cannot read image: {img_path}") |
| ok, buf = cv2.imencode(".jpg", img) |
| if not ok: |
| raise RuntimeError("cv2.imencode failed") |
| b64 = base64.b64encode(buf).decode("ascii") |
| return f"data:image/jpeg;base64,{b64}" |
|
|
|
|
| def test(openai_messages): |
| client = OpenAI(api_key="not-needed", base_url=BASE_URL) |
|
|
| stream = client.chat.completions.create( |
| model="AXERA-TECH/SmolVLM2-256M-Video-Instruct", |
| messages=openai_messages, |
| stream=True, |
| ) |
| out_chunks = [] |
| for ev in stream: |
| delta = ev.choices[0].delta |
| if delta and delta.content: |
| out_chunks.append(delta.content) |
| print(delta.content, end="", flush=True) |
| print() |
| assistant_text = "".join(out_chunks).strip() |
|
|
| def test_image(): |
| image_data = img_to_data_url("video/frame_0000.jpg") |
|
|
| openai_messages = { |
| "role": "user", |
| "content": [ |
| {"type": "text", "text": "Describe this image"}, |
| {"type": "image_url", "image_url": image_data}, |
| ], |
| } |
| |
|
|
| test(openai_messages) |
|
|
| def test_video(): |
| image_list = glob.glob("video/*.jpg") |
| image_list.sort() |
| |
| image_data_list = [img_to_data_url(img) for img in image_list] |
| |
| openai_messages = { |
| "role": "user", |
| "content": [ |
| {"type": "text", "text": "Describe this video"}, |
| {"type": "image_url", "is_video":True, "image_url": image_data_list}, |
| ], |
| } |
| |
| test(openai_messages) |
| |
| print("Test image") |
| test_image() |
| |
| print("Test video") |
| test_video() |
|
|
