use a better sample image

api_test.py

@@ -7,6 +7,8 @@ import torch
 from api_helper import preprocess_image, encode_numpy_array
 clip_image_size = 224
 num_steps = 1000
+test_image_url = "https://static.wixstatic.com/media/4d6b49_42b9435ce1104008b1b5f7a3c9bfcd69~mv2.jpg/v1/fill/w_454,h_333,fp_0.50_0.50,q_90/4d6b49_42b9435ce1104008b1b5f7a3c9bfcd69~mv2.jpg"
+
 
 client = Client("http://127.0.0.1:7860/")
 
@@ -21,7 +23,7 @@ def test_text():
 
 def test_image():
     result = client.predict(
-				"https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png",	# str representing filepath or URL to image in 'Image Prompt' Image component
+				test_image_url,	# str representing filepath or URL to image in 'Image Prompt' Image component
 				api_name="/image_to_embeddings"
     )
     return(result)
@@ -55,7 +57,6 @@ print("Number of predictions per second for image: ", 1 / average_time_seconds)
 
 
 
-test_image_url = "https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png"
 # download image from url
 import requests
 from PIL import Image
@@ -66,7 +67,6 @@ input_image = input_image.convert('RGB')
 # convert image to numpy array
 input_image = np.array(input_image)
 
-
 if input_image.shape[0] > clip_image_size or input_image.shape[1] > clip_image_size:
     input_image = preprocess_image(input_image, clip_image_size)
 payload = encode_numpy_array(input_image)