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Running
on
Zero
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# Standard library imports
# (Add any necessary imports for future object detection implementation)
# Third-party imports
from PIL import Image
import numpy as np
# Local imports
from utils.image_utils import load_image, preprocess_image
def object_detection(input_type, uploaded_image, image_url, base64_string):
"""
Performs object detection on the image from various input types.
Args:
input_type (str): The selected input method ("Upload File", "Enter URL", "Enter Base64").
uploaded_image (PIL.Image.Image): The uploaded image (if input_type is "Upload File").
image_url (str): The image URL (if input_type is "Enter URL").
base64_string (str): The image base64 string (if input_type is "Enter Base64").
Returns:
numpy.ndarray: The image with detected objects, or None if an error occurred.
"""
image = None
input_value = None
if input_type == "Upload File" and uploaded_image is not None:
image = uploaded_image # This is a PIL Image
print("Using uploaded image (PIL) for object detection") # Debug print
elif input_type == "Enter URL" and image_url and image_url.strip():
input_value = image_url
print(f"Using URL for object detection: {input_value}") # Debug print
elif input_type == "Enter Base64" and base64_string and base64_string.strip():
input_value = base64_string
print(f"Using Base64 string for object detection") # Debug print
else:
print("No valid input provided for object detection based on selected type.")
return None # No valid input
# If input_value is set (URL or Base64), use load_image
if input_value:
image = load_image(input_value)
if image is None:
return None # load_image failed
# Now 'image' should be a PIL Image or None
if image is None:
print("Image is None after loading/selection for object detection.")
return None
try:
# Preprocess the image (convert PIL to numpy, ensure RGB)
# preprocess_image expects a PIL Image or something convertible by Image.fromarray
processed_image = preprocess_image(image)
# TODO: Implement object detection logic here
# Currently just returns the processed image
print("Object detection logic placeholder executed.")
return processed_image
except Exception as e:
print(f"Error in object detection processing: {e}")
return None |