[Feature Added] > anomaly_gif_maker. This feature detects the frame where the pipeline thinks it is AI, converts it to gif and shows a side by side comparision to the Original Video, while also annotating the 'Peak Glitch' on the AI RADIANCE MAP gif

backend/app/ai/video/anomaly_gif_maker.py

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+import cv2
+import imageio
+import logging
+import os
+import uuid
+from typing import List
+import numpy as np
+
+logger = logging.getLogger(__name__)
+
+def generate_anomaly_gif(frames: List[np.ndarray], center_idx: int) -> str:
+    try:
+        save_dir = "uploads/video_heatmaps"
+        os.makedirs(save_dir, exist_ok=True)
+
+        safe_filename = f"{uuid.uuid4().hex}_anomaly_clip.gif"
+        save_path = os.path.join(save_dir, safe_filename)
+
+        start_idx = max(0, center_idx - 10)
+        end_idx = min(len(frames), center_idx + 10)
+
+        gif_frames = []
+
+        for i in range(start_idx, end_idx):
+            frame = frames[i]
+            
+            # 1. Take the grayscale X-Ray of the current frame
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            # 2. Extract sharp structural edges
+            laplacian = cv2.Laplacian(gray, cv2.CV_64F)
+            abs_laplacian = np.absolute(laplacian)
+            
+            # 3. Normalize to force the highest anomaly to glow at maximum brightness (255)
+            laplacian_8u = cv2.normalize(abs_laplacian, None, 0, 255, cv2.NORM_MINMAX, dtype=cv2.CV_8U)
+            # 4. Blur it to turn sharp noise into soft glowing clouds
+            heatmap_blurred = cv2.GaussianBlur(laplacian_8u, (15, 15), 0)
+            
+            # 5. Filter out natural background camera noise (anything under 70 brightness)
+            _, heatmap_mask = cv2.threshold(heatmap_blurred, 70, 255, cv2.THRESH_TOZERO)
+            # 6. Apply Jet Thermal Colors (Blue = natural, Red = AI Glitch)
+            colored_heatmap = cv2.applyColorMap(heatmap_mask, cv2.COLORMAP_JET)
+
+            # 7. Apply the thermal glow onto a copy of the video frame
+            heatmap_overlay = cv2.addWeighted(frame.copy(), 0.5, colored_heatmap, 0.7, 0)
+            
+            # 8. Find the contours (puddles) of the highest glowing areas and draw Red Boxes
+            _, thresh = cv2.threshold(laplacian_8u, 100, 255, cv2.THRESH_BINARY)
+            contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+            contours = sorted(contours, key=cv2.contourArea, reverse=True)[:3]
+            
+            for contour in contours:
+                if cv2.contourArea(contour) > 50:
+                    x, y, w, h = cv2.boundingRect(contour)
+                    cv2.rectangle(heatmap_overlay, (x, y), (x+w, y+h), (0, 0, 255), 2)
+            
+            # --- CREATE THE SIDE-BY-SIDE SPLIT SCREEN ---
+            
+            # 9. Resize both halves by 50% so the final GIF file size stays small
+            h, w = frame.shape[:2]
+            small_original = cv2.resize(frame, (w//2, h//2))
+            small_heatmap = cv2.resize(heatmap_overlay, (w//2, h//2))
+            
+            # 10. Add clear text labels to the top of both screens
+            cv2.putText(small_original, "ORIGINAL", (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
+            cv2.putText(small_heatmap, "AI RADIANCE MAP", (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)
+            
+            # 11. Add an extra flashing text warning when it reaches the absolute worst frame
+            if i == center_idx:
+                cv2.putText(small_heatmap, "PEAK GLITCH", (10, 55), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
+
+            # 12. Mathematically glue the two images together side-by-side using axis=1 (horizontal)
+            combined_frame = np.concatenate((small_original, small_heatmap), axis=1)
+            
+            # 13. Convert from BGR back to RGB before saving so the GIF colors aren't inverted
+            rgb_frame = cv2.cvtColor(combined_frame, cv2.COLOR_BGR2RGB)
+            gif_frames.append(rgb_frame)
+
+            # 13b. If this is the absolute peak glitch, append it 8 extra times to create a 1.2-second "Freeze-Frame" pause!
+            if i == center_idx:
+                for _ in range(8):
+                    gif_frames.append(rgb_frame)
+
+        # 14. Synthesize the final GIF animation (Slowed down to ~6.5fps for better readability, and loop=0 for infinite looping)
+        imageio.mimsave(save_path, gif_frames, format='GIF', duration=5, loop=0)
+
+        return save_path
+
+    except Exception as e:
+        logger.error(f"Failed to generate Anomaly GIF Clip: {str(e)}")
+        return None