8f05a7c188
- Update ASR, face, OCR, pose processors - Add release pre-flight check script - Add synonym generation, chunk processing scripts - Add face recognition, stamp search utilities
87 lines
2.7 KiB
Python
87 lines
2.7 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Search for magnifying glass in key stamp scenes using OWL-ViT
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"""
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import os
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import cv2
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import json
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from PIL import Image
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import torch
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from transformers import OwlViTProcessor, OwlViTForObjectDetection
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BASE_DIR = "output/384b0ff44aaaa1f1/magnifying_glass"
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RESULTS_DIR = "output/384b0ff44aaaa1f1/magnifying_glass_results"
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os.makedirs(RESULTS_DIR, exist_ok=True)
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print("🔬 Loading OWL-ViT...")
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processor = OwlViTProcessor.from_pretrained("google/owlvit-base-patch32")
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model = OwlViTForObjectDetection.from_pretrained("google/owlvit-base-patch32")
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model.eval()
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SEARCH_TERMS = [
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"magnifying glass",
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"magnifier",
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"loupe",
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"lens",
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"looking glass",
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"glass",
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"round glass",
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]
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import glob
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frames = sorted(glob.glob(os.path.join(BASE_DIR, "mag_*.jpg")))
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print(f"🔍 Searching {len(frames)} frames for magnifying glass...")
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found = False
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for frame_path in frames:
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frame_name = os.path.basename(frame_path)
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sec = frame_name.replace("mag_", "").replace("s.jpg", "")
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image = Image.open(frame_path).convert("RGB")
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for term in SEARCH_TERMS:
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inputs = processor(text=[[term]], images=image, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs)
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target_sizes = torch.Tensor([image.size[::-1]])
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results = processor.post_process_object_detection(
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outputs=outputs, target_sizes=target_sizes, threshold=0.05
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)
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for score, label, box in zip(
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results[0]["scores"], results[0]["labels"], results[0]["boxes"]
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):
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s = float(score)
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if s > 0.05:
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x1, y1, x2, y2 = map(int, box.tolist())
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img = cv2.imread(frame_path)
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crop = img[y1:y2, x1:x2]
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if crop.size > 0:
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crop_name = f"mag_{sec}s_{term.replace(' ', '_')}_{s:.2f}.jpg"
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cv2.imwrite(os.path.join(RESULTS_DIR, crop_name), crop)
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cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 3)
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cv2.putText(
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img,
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f"{term} {s:.2f}",
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(x1, y1 - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.7,
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(0, 255, 0),
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2,
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)
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ann_name = f"annotated_mag_{sec}s.jpg"
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cv2.imwrite(os.path.join(RESULTS_DIR, ann_name), img)
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print(f" 📍 {sec}s | {term} | {s:.2f}")
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found = True
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if not found:
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print("❌ No magnifying glass detected in these frames.")
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else:
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print(f"\n✅ Found magnifying glass detections. Check {RESULTS_DIR}")
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