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Don't resize output image
#2
by
ceyda
- opened
app.py
CHANGED
@@ -19,19 +19,22 @@ processor = OwlViTProcessor.from_pretrained("google/owlvit-base-patch32")
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def query_image(img, text_queries, score_threshold):
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text_queries = text_queries
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text_queries = text_queries.split(",")
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-
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with torch.no_grad():
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outputs = model(**inputs)
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outputs.logits = outputs.logits.cpu()
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outputs.pred_boxes = outputs.pred_boxes.cpu()
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results = processor.post_process(outputs=outputs, target_sizes=target_sizes)
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boxes, scores, labels = results[0]["boxes"], results[0]["scores"], results[0]["labels"]
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img = cv2.resize(img, (768, 768), interpolation = cv2.INTER_AREA)
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font = cv2.FONT_HERSHEY_SIMPLEX
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for box, score, label in zip(boxes, scores, labels):
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@@ -61,7 +64,7 @@ can also use the score threshold slider to set a threshold to filter out low pro
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"""
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demo = gr.Interface(
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query_image,
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inputs=[gr.Image(
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outputs="image",
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title="Zero-Shot Object Detection with OWL-ViT",
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description=description,
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def query_image(img, text_queries, score_threshold):
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text_queries = text_queries
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text_queries = text_queries.split(",")
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target_sizes = torch.Tensor([img.shape[:2]])
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img_input = cv2.resize(img, (768, 768), interpolation = cv2.INTER_AREA)
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inputs = processor(text=text_queries, images=img_input, return_tensors="pt").to(device)
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with torch.no_grad():
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outputs = model(**inputs)
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outputs.logits = outputs.logits.cpu()
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outputs.pred_boxes = outputs.pred_boxes.cpu()
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results = processor.post_process(outputs=outputs, target_sizes=target_sizes)
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boxes, scores, labels = results[0]["boxes"], results[0]["scores"], results[0]["labels"]
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font = cv2.FONT_HERSHEY_SIMPLEX
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for box, score, label in zip(boxes, scores, labels):
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"""
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demo = gr.Interface(
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query_image,
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inputs=[gr.Image(), "text", gr.Slider(0, 1, value=0.1)],
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outputs="image",
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title="Zero-Shot Object Detection with OWL-ViT",
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description=description,
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