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manga-whisperer.py

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+from transformers import AutoModel
+import numpy as np
+from PIL import Image
+import torch
+import os
+
+images = [
+    "1.png",
+    "1.jpg",
+]
+
+
+def read_image_as_np_array(image_path):
+    with open(image_path, "rb") as file:
+        image = Image.open(file).convert("L").convert("RGB")
+        image = np.array(image)
+    return image
+
+
+images = [read_image_as_np_array(image) for image in images]
+
+model = AutoModel.from_pretrained(
+    "ragavsachdeva/magi", trust_remote_code=True).cuda()
+# model = AutoModel.from_pretrained(
+#     "./magi", trust_remote_code=True).cuda()
+with torch.no_grad():
+    results = model.predict_detections_and_associations(images)
+    text_bboxes_for_all_images = [x["texts"] for x in results]
+    ocr_results = model.predict_ocr(images, text_bboxes_for_all_images)
+
+for i in range(len(images)):
+    model.visualise_single_image_prediction(
+        images[i], results[i], filename=f"image_{i}.png")
+    model.generate_transcript_for_single_image(
+        results[i], ocr_results[i], filename=f"transcript_{i}.txt")

requirements.txt

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+transformers
+einops
+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+shapely
+timm
+scipy
+tokenizers