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| import gradio as gr | |
| import requests | |
| from PIL import Image | |
| from sentence_transformers import SentenceTransformer, util | |
| # define model | |
| model_sentence = SentenceTransformer('clip-ViT-B-32') | |
| # functions | |
| def download_images(url): | |
| ''' | |
| This function: | |
| 1. takes in a URL | |
| 2. downloads the raw content (image) | |
| 3. reads this image out | |
| 4. returns temp img, HTTP status code and flag | |
| ''' | |
| try: | |
| # request image | |
| response = requests.get(url, stream=True, timeout=3.5).raw | |
| # request status code (can't be done with .raw) | |
| status_code = requests.get(url).status_code | |
| # read in image | |
| image = Image.open(response) | |
| # convert all images to rgb -> case png is in rgba format | |
| rgb_im = image.convert('RGB') | |
| # return temp image, status code and flag | |
| return rgb_im, status_code, 0 | |
| except: | |
| print("error", status_code) | |
| # error flag | |
| return "error url", "", -1 | |
| def clip_sim_preds(url, text): | |
| ''' | |
| This function: | |
| 1. Takes in an URL/Text/ID pair | |
| 2. Calls download images | |
| 3. Receives a temp image | |
| 4. Feeds the image/text-pair into the defined clip model | |
| 5. returns calculated similarities | |
| ''' | |
| # call download images | |
| image, status_code, flag = download_images(url) | |
| # if no error occured and temp image successfully downloaded, proceed | |
| if flag == 0: | |
| try: | |
| # Encode an image: | |
| img_emb = model_sentence.encode(image) | |
| # Encode text descriptions | |
| text_emb = model_sentence.encode([text]) | |
| # Compute cosine similarities | |
| cos_scores = util.cos_sim(img_emb, text_emb) | |
| # return the predicted similarity, flag | |
| return cos_scores.item() | |
| except: | |
| return "error clip_si" | |
| # if error occured, indicate this with -1 flag | |
| else: | |
| return "error" | |
| article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/samueldomdey/ClipCosineSimilarityUpload' target='_blank'>Alternative</a></p>" | |
| # define app | |
| # takes in url of an image and a corresponding text, computes and returns cosine similarity | |
| gr.Interface(clip_sim_preds, | |
| inputs=[gr.inputs.Textbox(lines=1, placeholder=None, default="http://images.cocodataset.org/val2017/000000039769.jpg", label="URL", optional=False), | |
| gr.inputs.Textbox(lines=1, placeholder=None, default="two cats with black stripes on a purple blanket, tv remotes, green collar", label="Text", optional=False)], | |
| outputs=[gr.outputs.Textbox(type="auto", label="Cosine similarity")], | |
| theme="huggingface", | |
| title="Clip Cosine similarity", | |
| description="Clip cosine similarity of an image/text pair", | |
| article=article, | |
| allow_flagging=False,).launch(debug=True) | |