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| import gradio as gr | |
| from PIL import Image, ImageDraw, ImageFont | |
| # Use a pipeline as a high-level helper | |
| from transformers import pipeline | |
| object_detector = pipeline("object-detection", model="facebook/detr-resnet-101-dc5") | |
| def draw_bounding_boxes(image, detections, font_path=None, font_size=20): | |
| """ | |
| Draws bounding boxes on the given image based on the detections. | |
| :param image: PIL.Image object | |
| :param detections: List of detection results, where each result is a dictionary containing | |
| 'score', 'label', and 'box' keys. 'box' itself is a dictionary with 'xmin', | |
| 'ymin', 'xmax', 'ymax'. | |
| :param font_path: Path to the TrueType font file to use for text. | |
| :param font_size: Size of the font to use for text. | |
| :return: PIL.Image object with bounding boxes drawn. | |
| """ | |
| # Make a copy of the image to draw on | |
| draw_image = image.copy() | |
| draw = ImageDraw.Draw(draw_image) | |
| # Load custom font or default font if path not provided | |
| if font_path: | |
| font = ImageFont.truetype(font_path, font_size) | |
| else: | |
| # When font_path is not provided, load default font but it's size is fixed | |
| font = ImageFont.load_default() | |
| # Increase font size workaround by using a TTF font file, if needed, can download and specify the path | |
| for detection in detections: | |
| box = detection['box'] | |
| xmin = box['xmin'] | |
| ymin = box['ymin'] | |
| xmax = box['xmax'] | |
| ymax = box['ymax'] | |
| # Draw the bounding box | |
| draw.rectangle([(xmin, ymin), (xmax, ymax)], outline="red", width=3) | |
| # Optionally, you can also draw the label and score | |
| label = detection['label'] | |
| score = detection['score'] | |
| text = f"{label} {score:.2f}" | |
| # Draw text with background rectangle for visibility | |
| if font_path: # Use the custom font with increased size | |
| text_size = draw.textbbox((xmin, ymin), text, font=font) | |
| else: | |
| # Calculate text size using the default font | |
| text_size = draw.textbbox((xmin, ymin), text) | |
| draw.rectangle([(text_size[0], text_size[1]), (text_size[2], text_size[3])], fill="red") | |
| draw.text((xmin, ymin), text, fill="white", font=font) | |
| return draw_image | |
| def detect_object(image): | |
| raw_image = image | |
| output = object_detector(raw_image) | |
| processed_image = draw_bounding_boxes(raw_image, output) | |
| return processed_image | |
| demo = gr.Interface(fn=detect_object, | |
| inputs=[gr.Image(label="Bild auswählen",type="pil")], | |
| outputs=[gr.Image(label="Verarbeitetes Bild", type="pil")], | |
| title="Project 6: Objekt-Detektor", | |
| description="DIESE ANWENDUNG WIRD VERWENDET, UM OBJEKTE IN DEM ANGEGEBENEN EINGABEBILD ZU ERKENNEN.", | |
| allow_flagging="never", | |
| submit_btn="Übermitteln", | |
| clear_btn="Bereinigen") | |
| demo.launch() | |