86830019ad
- Add IPFSHLSOutput class that uploads segments to IPFS as they're created - Update streaming task to use IPFS HLS output for distributed streaming - Add /ipfs-stream endpoint to get IPFS playlist URL - Update /stream endpoint to redirect to IPFS when available - Add GPU persistence mode (STREAMING_GPU_PERSIST=1) to keep frames on GPU - Add hardware video decoding (NVDEC) support for faster video processing - Add GPU-accelerated primitive libraries: blending_gpu, color_ops_gpu, geometry_gpu - Add streaming_gpu module with GPUFrame class for tracking CPU/GPU data location - Add Dockerfile.gpu for building GPU-enabled worker image Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
151 lines
3.7 KiB
Python
151 lines
3.7 KiB
Python
"""
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Image Primitives Library
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Basic image operations: dimensions, pixels, resize, crop, paste.
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"""
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import numpy as np
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import cv2
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def prim_width(img):
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if isinstance(img, (list, tuple)):
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raise TypeError(f"image:width expects an image array, got {type(img).__name__} with {len(img)} elements")
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return img.shape[1]
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def prim_height(img):
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if isinstance(img, (list, tuple)):
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import sys
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print(f"DEBUG image:height got list: {img[:3]}... (types: {[type(x).__name__ for x in img[:3]]})", file=sys.stderr)
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raise TypeError(f"image:height expects an image array, got {type(img).__name__} with {len(img)} elements: {img}")
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return img.shape[0]
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def prim_make_image(w, h, color=None):
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"""Create a new image filled with color (default black)."""
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if color is None:
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color = [0, 0, 0]
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img = np.zeros((h, w, 3), dtype=np.uint8)
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img[:] = color
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return img
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def prim_copy(img):
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return img.copy()
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def prim_pixel(img, x, y):
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"""Get pixel color at (x, y) as [r, g, b]."""
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h, w = img.shape[:2]
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if 0 <= x < w and 0 <= y < h:
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return list(img[int(y), int(x)])
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return [0, 0, 0]
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def prim_set_pixel(img, x, y, color):
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"""Set pixel at (x, y) to color, returns modified image."""
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result = img.copy()
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h, w = result.shape[:2]
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if 0 <= x < w and 0 <= y < h:
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result[int(y), int(x)] = color
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return result
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def prim_sample(img, x, y):
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"""Bilinear sample at float coordinates, returns [r, g, b] as floats."""
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h, w = img.shape[:2]
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x = max(0, min(w - 1.001, x))
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y = max(0, min(h - 1.001, y))
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x0, y0 = int(x), int(y)
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x1, y1 = min(x0 + 1, w - 1), min(y0 + 1, h - 1)
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fx, fy = x - x0, y - y0
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c00 = img[y0, x0].astype(float)
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c10 = img[y0, x1].astype(float)
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c01 = img[y1, x0].astype(float)
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c11 = img[y1, x1].astype(float)
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top = c00 * (1 - fx) + c10 * fx
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bottom = c01 * (1 - fx) + c11 * fx
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return list(top * (1 - fy) + bottom * fy)
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def prim_channel(img, c):
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"""Extract single channel (0=R, 1=G, 2=B)."""
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return img[:, :, c]
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def prim_merge_channels(r, g, b):
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"""Merge three single-channel arrays into RGB image."""
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return np.stack([r, g, b], axis=2).astype(np.uint8)
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def prim_resize(img, w, h, mode="linear"):
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"""Resize image to w x h."""
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interp = cv2.INTER_LINEAR
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if mode == "nearest":
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interp = cv2.INTER_NEAREST
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elif mode == "cubic":
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interp = cv2.INTER_CUBIC
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elif mode == "area":
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interp = cv2.INTER_AREA
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return cv2.resize(img, (int(w), int(h)), interpolation=interp)
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def prim_crop(img, x, y, w, h):
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"""Crop rectangle from image."""
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x, y, w, h = int(x), int(y), int(w), int(h)
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ih, iw = img.shape[:2]
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x = max(0, min(x, iw - 1))
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y = max(0, min(y, ih - 1))
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w = min(w, iw - x)
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h = min(h, ih - y)
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return img[y:y+h, x:x+w].copy()
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def prim_paste(dst, src, x, y):
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"""Paste src onto dst at position (x, y)."""
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result = dst.copy()
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x, y = int(x), int(y)
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sh, sw = src.shape[:2]
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dh, dw = dst.shape[:2]
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# Clip to bounds
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sx1 = max(0, -x)
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sy1 = max(0, -y)
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dx1 = max(0, x)
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dy1 = max(0, y)
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sx2 = min(sw, dw - x)
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sy2 = min(sh, dh - y)
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if sx2 > sx1 and sy2 > sy1:
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result[dy1:dy1+(sy2-sy1), dx1:dx1+(sx2-sx1)] = src[sy1:sy2, sx1:sx2]
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return result
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PRIMITIVES = {
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# Dimensions
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'width': prim_width,
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'height': prim_height,
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# Creation
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'make-image': prim_make_image,
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'copy': prim_copy,
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# Pixel access
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'pixel': prim_pixel,
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'set-pixel': prim_set_pixel,
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'sample': prim_sample,
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# Channels
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'channel': prim_channel,
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'merge-channels': prim_merge_channels,
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# Geometry
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'resize': prim_resize,
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'crop': prim_crop,
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'paste': prim_paste,
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}
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