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
90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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Debug OWL-ViT with Multiple Prompts
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"""
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import os
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import cv2
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import torch
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from PIL import Image
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from transformers import OwlViTProcessor, OwlViTForObjectDetection
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UUID = "384b0ff44aaaa1f1"
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VIDEO_PATH = f"output/{UUID}/{UUID}.mp4"
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OUTPUT_DIR = f"output/{UUID}/owl_vit_results_debug"
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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print("🧠 Loading OWL-ViT model...")
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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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cap = cv2.VideoCapture(VIDEO_PATH)
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# Frames we want to check
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timestamps = [5851.6, 5860.4, 6756.6, 6846.0]
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# Prompts to try
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prompts = [
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["a postage stamp", "a stamp"],
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["a letter", "an envelope", "a piece of paper"],
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["a small square paper"],
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]
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for t in timestamps:
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cap.set(cv2.CAP_PROP_POS_MSEC, t * 1000)
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ret, frame = cap.read()
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if not ret:
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continue
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image_pil = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
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# Try different prompt sets
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found_any = False
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for i, text_queries in enumerate(prompts):
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inputs = processor(text=text_queries, images=image_pil, return_tensors="pt")
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outputs = model(**inputs)
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target_sizes = torch.Tensor([image_pil.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 box, score, label in zip(
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results[0]["boxes"], results[0]["scores"], results[0]["labels"]
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):
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if score > 0.05:
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found_any = True
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x_min, y_min, x_max, y_max = box.int().tolist()
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label_text = text_queries[label.item()]
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print(f" 🟢 Found '{label_text}' ({score.item():.3f}) at {t:.2f}s")
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# Draw
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cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)
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cv2.putText(
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frame,
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f"{label_text} {score.item():.3f}",
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(x_min, y_min - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.5,
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(0, 255, 0),
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1,
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)
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if not found_any:
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print(f" 🔴 Nothing found at {t:.2f}s")
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cv2.putText(
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frame,
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"NO DETECTIONS",
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(50, 50),
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cv2.FONT_HERSHEY_SIMPLEX,
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1,
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(0, 0, 255),
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2,
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)
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else:
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# Save result
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save_path = os.path.join(OUTPUT_DIR, f"detected_{int(t)}.jpg")
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cv2.imwrite(save_path, frame)
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print(f" 💾 Saved to {save_path}")
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cap.release()
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