update demo example
Browse files- demo.ipynb +19 -4
demo.ipynb
CHANGED
@@ -193,16 +193,24 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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"source": [
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"import requests\n",
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"from PIL import Image\n",
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"img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'\n",
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"raw_image = Image.open(requests.get(img_url, stream=True).raw)
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"query = \"how many dogs are in the picture?\"\n",
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"inputs = image_processor([
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"prompt = apply_prompt_template(query)\n",
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"language_inputs = tokenizer([prompt], return_tensors=\"pt\")\n",
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"inputs.update(language_inputs)\n",
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@@ -216,6 +224,13 @@
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"print(\"==> prediciton: \", prediction)\n",
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"# output: ==> prediciton: There is one dog in the picture."
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]
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}
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],
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"metadata": {
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"==> prediciton: There is one dog in the picture.\n"
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]
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}
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],
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"source": [
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"import requests\n",
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"from PIL import Image\n",
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"img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'\n",
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"raw_image = Image.open(requests.get(img_url, stream=True).raw)\n",
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"query = \"how many dogs are in the picture?\"\n",
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"inputs = image_processor([raw_image], return_tensors=\"pt\", image_aspect_ratio='anyres')\n",
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"prompt = apply_prompt_template(query)\n",
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"language_inputs = tokenizer([prompt], return_tensors=\"pt\")\n",
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"inputs.update(language_inputs)\n",
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"print(\"==> prediciton: \", prediction)\n",
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"# output: ==> prediciton: There is one dog in the picture."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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