Add GPU image primitives (gpu-make-image, gpu-gradient)

sexp_effects/primitive_libs/streaming_gpu.py

@@ -1035,7 +1035,78 @@ def prim_autonomous_pipeline(img, effects_list, dynamic_expressions, frame_num,
     return pipeline(gpu_img, int(frame_num), float(fps))
 
 
+# ============================================================
+# GPU Image Primitives (keep images on GPU)
+# ============================================================
+
+def gpu_make_image(w, h, color=None):
+    """Create a new image on GPU filled with color (default black).
+
+    Unlike image:make-image, this keeps the image on GPU memory,
+    avoiding CPU<->GPU transfers in the pipeline.
+    """
+    if not GPU_AVAILABLE:
+        # Fallback to CPU
+        import numpy as np
+        if color is None:
+            color = [0, 0, 0]
+        img = np.zeros((int(h), int(w), 3), dtype=np.uint8)
+        img[:] = color
+        return img
+
+    w, h = int(w), int(h)
+    if color is None:
+        color = [0, 0, 0]
+
+    # Create on GPU directly
+    img = cp.zeros((h, w, 3), dtype=cp.uint8)
+    img[:, :, 0] = int(color[0]) if len(color) > 0 else 0
+    img[:, :, 1] = int(color[1]) if len(color) > 1 else 0
+    img[:, :, 2] = int(color[2]) if len(color) > 2 else 0
+
+    return img
+
+
+def gpu_gradient_image(w, h, color1=None, color2=None, direction='horizontal'):
+    """Create a gradient image on GPU.
+
+    Args:
+        w, h: Dimensions
+        color1, color2: Start and end colors [r, g, b]
+        direction: 'horizontal', 'vertical', 'diagonal'
+    """
+    if not GPU_AVAILABLE:
+        return gpu_make_image(w, h, color1)
+
+    w, h = int(w), int(h)
+    if color1 is None:
+        color1 = [0, 0, 0]
+    if color2 is None:
+        color2 = [255, 255, 255]
+
+    img = cp.zeros((h, w, 3), dtype=cp.uint8)
+
+    if direction == 'horizontal':
+        for c in range(3):
+            grad = cp.linspace(color1[c], color2[c], w, dtype=cp.float32)
+            img[:, :, c] = grad[cp.newaxis, :].astype(cp.uint8)
+    elif direction == 'vertical':
+        for c in range(3):
+            grad = cp.linspace(color1[c], color2[c], h, dtype=cp.float32)
+            img[:, :, c] = grad[:, cp.newaxis].astype(cp.uint8)
+    elif direction == 'diagonal':
+        for c in range(3):
+            x_grad = cp.linspace(0, 1, w, dtype=cp.float32)[cp.newaxis, :]
+            y_grad = cp.linspace(0, 1, h, dtype=cp.float32)[:, cp.newaxis]
+            combined = (x_grad + y_grad) / 2
+            img[:, :, c] = (color1[c] + (color2[c] - color1[c]) * combined).astype(cp.uint8)
+
+    return img
+
+
 # Add GPU-specific primitives
 PRIMITIVES['fused-pipeline'] = prim_fused_pipeline
 PRIMITIVES['autonomous-pipeline'] = prim_autonomous_pipeline
+PRIMITIVES['gpu-make-image'] = gpu_make_image
+PRIMITIVES['gpu-gradient'] = gpu_gradient_image
 # (The GPU video source will be added by create_cid_primitives in the task)

test_autonomous.sexp

@@ -27,10 +27,10 @@
      :ripple_phase "t * 2.0f"
      :brightness_factor "0.8f + 0.4f * sinf(t * 2.0f)"})
 
-  ;; Frame pipeline - creates image and applies autonomous pipeline
+  ;; Frame pipeline - creates image ON GPU and applies autonomous pipeline
   (frame
-    (let [;; Create base gradient (still needs Python for now)
-          base (image:make-image 1920 1080 [128 100 200])]
+    (let [;; Create base image ON GPU (no CPU involvement!)
+          base (streaming_gpu:gpu-make-image 1920 1080 [128 100 200])]
 
       ;; Apply autonomous pipeline - ALL EFFECTS + ALL MATH ON GPU!
       (streaming_gpu:autonomous-pipeline base effects expressions frame-num 30.0))))