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import requests | |
# Define base URL for your Hugging Face Space | |
BASE_URL = "https://danilohssantana-qwen2-5-vl-api.hf.space" | |
# Image URL to be encoded | |
image_url = "https://cdn.britannica.com/35/238335-050-2CB2EB8A/Lionel-Messi-Argentina-Netherlands-World-Cup-Qatar-2022.jpg" | |
# Step 1: Download the image | |
response = requests.get(image_url) | |
if response.status_code != 200: | |
print("Error downloading image:", response.status_code, response.text) | |
exit() | |
# Step 2: Send the image to the encode-image endpoint | |
files = {"file": ("image.jpg", response.content, "image/jpeg")} | |
encode_response = requests.post(f"{BASE_URL}/encode-image/", files=files) | |
if encode_response.status_code != 200: | |
print("Error encoding image:", encode_response.status_code, encode_response.text) | |
exit() | |
encoded_image = encode_response.json().get("encoded_image") | |
# Step 3: Send the encoded image to the predict endpoint | |
predict_payload = { | |
"image_base64": encoded_image, | |
"prompt": "describe the image", | |
} | |
print("Payload:", predict_payload) | |
predict_response = requests.post(f"{BASE_URL}/predict", json=predict_payload) | |
# # Step 4: Print the response | |
if predict_response.status_code == 200: | |
print("Response:", predict_response.json()) | |
else: | |
print("Error:", predict_response.status_code, predict_response.text) | |