Update app.py

app.py

@@ -27,10 +27,6 @@ MIN_REP_SECONDS = 0.33
 # Prevents very long false reps when tracking fails.
 MAX_REP_SECONDS = 8.0
 
-# Downscale only (no crop) for YOLO inference
-# 640 is a safe default across varying camera angles.
-MAX_INFER_SIDE = 640
-
 
 # ----------------------------
 # Load YOLO pose model (lazy)
@@ -106,17 +102,6 @@ def likelihood_to_score(p):
             return int(round(s_lo + t * (s_hi - s_lo)))
     return 0
 
-def resize_for_inference(frame, max_side=640):
-    """Downscale only (no crop) to speed YOLO. Keeps aspect ratio."""
-    h, w = frame.shape[:2]
-    m = max(h, w)
-    if m <= max_side:
-        return frame
-    scale = max_side / float(m)
-    new_w = int(round(w * scale))
-    new_h = int(round(h * scale))
-    return cv2.resize(frame, (new_w, new_h), interpolation=cv2.INTER_AREA)
-
 
 # ----------------------------
 # Core pipeline
@@ -146,8 +131,7 @@ def analyze_pushup_video_yolo(video_path: str, out_dir: str):
     print(
         f"[speed] video_fps={fps:.2f} target_fps={TARGET_FPS:.2f} "
         f"stride={frame_stride} effective_fps={effective_fps:.2f} "
-        f"min_rep_frames={min_rep_frames} max_rep_frames={max_rep_frames} "
-        f"infer_max_side={MAX_INFER_SIDE}"
+        f"min_rep_frames={min_rep_frames} max_rep_frames={max_rep_frames}"
     )
 
     # 1) First pass: compute angles + confs per sampled frame
@@ -163,9 +147,7 @@ def analyze_pushup_video_yolo(video_path: str, out_dir: str):
             frame_i += 1
             continue
 
-        infer_frame = resize_for_inference(frame, MAX_INFER_SIDE)
-
-        res = model(infer_frame, verbose=False)[0]
+        res = model(frame, verbose=False)[0]
         if res.keypoints is None or len(res.keypoints.xy) == 0:
             angles.append(np.nan)
             confs.append(0.0)
@@ -211,7 +193,7 @@ def analyze_pushup_video_yolo(video_path: str, out_dir: str):
     elif not np.any(mask):
         raise RuntimeError("No valid pose angles detected.")
 
-    # Smooth (updated to match our efficient logic: ~1 second window scaled by effective_fps)
+    # Smooth (match our efficient logic: ~1 second window scaled by effective_fps)
     win = int(round(effective_fps * 1.0))
     win = max(5, win)
     if win % 2 == 0:
@@ -219,7 +201,7 @@ def analyze_pushup_video_yolo(video_path: str, out_dir: str):
     win = min(win, (len(angles) // 2) * 2 + 1)
     angles_smooth = savgol_filter(angles, win, 2)
 
-    # 2) Rep detection on smoothed angles (updated to match our efficient logic)
+    # 2) Rep detection on smoothed angles (match our efficient logic)
     reps = []
     state = "WAIT_DOWN"
     rep_min = rep_max = rep_conf_sum = rep_len = rep_start = None
@@ -320,7 +302,6 @@ def analyze_pushup_video_yolo(video_path: str, out_dir: str):
             "frame_stride": int(frame_stride),
             "effective_fps": float(effective_fps),
             "min_rep_frames": int(min_rep_frames),
-            "max_infer_side": int(MAX_INFER_SIDE),
         }
     }
 
@@ -384,4 +365,4 @@ with gr.Blocks(title="Pushup API (YOLO)") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()