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| import gradio as gr | |
| import subprocess | |
| from PIL import Image | |
| import tempfile | |
| import os | |
| import yaml | |
| def resize_image(image, base_height): | |
| # Calculate aspect ratio | |
| w_percent = base_height / float(image.size[1]) | |
| w_size = int(float(image.size[0]) * float(w_percent)) | |
| # Resize the image | |
| return image.resize((w_size, base_height), Image.Resampling.LANCZOS) | |
| def predict(input_image: Image.Image): | |
| try: | |
| # Try to resize the image to a fixed height of 128 pixels | |
| try: | |
| input_image = resize_image(input_image, 128) | |
| except Exception as e: | |
| print(f"Image resizing failed: {e}") | |
| return f"Image resizing failed: {e}" | |
| # Used as a context manager. Takes care of cleaning up the directory. | |
| # Even if an error is raised within the with block, the directory is removed. | |
| # No finally block needed | |
| with tempfile.TemporaryDirectory() as temp_dir: | |
| temp_image_path = os.path.join(temp_dir, 'temp_image.jpg') | |
| temp_list_path = os.path.join(temp_dir, 'temp_img_list.txt') | |
| temp_config_path = os.path.join(temp_dir, 'temp_config.yaml') | |
| input_image.save(temp_image_path) | |
| # Create a temporary img_list file | |
| with open(temp_list_path, 'w') as f: | |
| f.write(temp_image_path) | |
| # Read the original config file and create a temporary one | |
| with open('my_decode_config.yaml', 'r') as f: | |
| config_data = yaml.safe_load(f) | |
| config_data['img_list'] = temp_list_path | |
| with open(temp_config_path, 'w') as f: | |
| yaml.dump(config_data, f) | |
| try: | |
| subprocess.run(f"pylaia-htr-decode-ctc --config {temp_config_path} | tee predict.txt", shell=True, check=True) | |
| except subprocess.CalledProcessError as e: | |
| print(f"Command failed with error {e.returncode}, output:\n{e.output}") | |
| # subprocess.run(f"pylaia-htr-decode-ctc --config {temp_config_path} | tee predict.txt", shell=True, check=True) | |
| # Alternative to shell=True (ChatGPT suggestion) | |
| # from subprocess import Popen, PIPE | |
| # # Run the first command and capture its output | |
| # p1 = Popen(["pylaia-htr-decode-ctc", "--config", temp_config_path], stdout=PIPE) | |
| # output = p1.communicate()[0] | |
| # # Write the output to predict.txt | |
| # with open('predict.txt', 'wb') as f: | |
| # f.write(output) | |
| # Read the output from predict.txt | |
| if os.path.exists('predict.txt'): | |
| with open('predict.txt', 'r') as f: | |
| output_line = f.read().strip().split('\n')[-1] # Last line | |
| _, prediction = output_line.split(' ', 1) # split only at the first space | |
| else: | |
| print('predict.txt does not exist') | |
| return prediction | |
| except subprocess.CalledProcessError as e: | |
| return f"Command failed with error {e.returncode}" | |
| # Gradio interface | |
| title = "PyLaia HTR" | |
| description = "Inference using PyLaia models." | |
| examples = [["examples/example01.jpg"], ["examples/example02.jpg"]] | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.inputs.Image(type="pil"), | |
| outputs=gr.outputs.Textbox(), | |
| title=title, | |
| description=description, | |
| examples=examples | |
| ) | |
| iface.launch() | |